In this paper, the development and experimental validation of a novel double two-loop nonlinear controller based on adaptive neural networks for a quadrotor are presented. The proposed controller has a two-loop structure: an outer loop for position control and an inner loop for attitude control. Similarly, both position and orientation controllers also have a two-loop design with an adaptive neural network in each inner loop. The output weight matrices of the neural networks are updated online through adaptation laws obtained from a rigorous error convergence analysis. Thus, a training stage is unnecessary prior to the neural network implementation. Additionally, an integral action is included in the controller to cope with constant disturbances. The error convergence analysis guarantees the achievement of the trajectory tracking task and the boundedness of the output weight matrix estimation errors. The proposed scheme is designed such that an accurate knowledge of the quadrotor parameters is not needed. A comparison against the proposed controller and two other well-known schemes is presented. The obtained results showed the functionality of the proposed controller and demonstrated robustness to parametric uncertainty.

This article presents the design of a fault diagnosis strategy to deal with faults in multiple actuators in a quad-rotor under the influence of external disturbances. The faults are modeled as partial loss of effectiveness. The proposed fault diagnosis strategy is based on a finite-time sliding-mode observer that estimates the full state and provides a set of residuals using only the output information. Moreover, such a strategy is able to detect, isolate, and identify faults in multiple actuators despite the presence of external disturbances. Experimental results on the Quanser’s QBall 2 platform show the performance of the proposed scheme.

In this paper, an actuator fault accommodation controller is developed to solve the trajectory tracking problem in Quad-Rotors under the effects of faults in multiple actuators and external disturbances. The faults are modeled as partial loss of effectiveness. The proposed fault accommodation approach is composed of a fault identification module and a baseline robust-nominal controller. The fault identification module is based on a finite-time sliding-mode observer that provides a set of residuals using only the output information. The fault accommodation strategy uses fault identification to partially compensate the actuator faults allowing the usage of a baseline robust-nominal controller that deals with the external disturbances. Numerical simulations show the performance of the proposed control strategy.

This paper studies a particular Unmanned Aerial Vehicle (UAV), called QBall 2+ quadcopter. This vehicle is a complex system, non-linear, strongly coupled, and under-actuated. First, a non-linear model was developed to represent the dynamics of the studied drone. Once the latter is established, the linear model was used to obtain the best gains of the Proportional Integral Derivative (PID) controller. This controller was applied after on the non-linear model of the UAV. Moreover, a Sliding Mode Controller (SMC) based on Sliding Mode Observer (SMO) was designed for retrieving the system unknown variables. Through these latter, the QBall 2+ was controlled, taking into account the observer errors. The first contribution in this work is to implement the PID regulator on the QBall 2+ flight controller to validate the results obtained by simulation. Secondly, due to the limitations of the Flex 3 cameras, especially when the drone is outside their working environment, the sliding mode observer was implemented to replace the cameras in order to measure the states of the system considered in this work. Simulation results of the different applied controllers were displayed to evaluate their effectiveness.

In this work, we establish a convenient similarity between an adaptive backstepping control law and a standard proportional-integral-derivative (PID) controller for a class of second-order systems. The extracted similarity provides a deeper understanding of the adaptive backstepping design from a performance perspective via an intuitive method to select its otherwise abstract controller gains, on top of its traditional stability perspective. Such a similarity analysis opens the door for researchers to use well-established PID tuning methods to predict the performance of Lyapunov stability-based controllers. At the same time, the obtained formulation reveals how the corresponding PID control law can be linked to Lyapunov stability theory.

@article{wang3_2020,
title = {A dual adaptive fault-tolerant control for a quadrotor helicopter against actuator faults and model uncertainties without overestimation},
author = {Wang, B.; Yu, X.; Mu, L.; Zhang, Y.},
journal = {Aerospace Science and Technology},
year = {2020},
month = {4},
volume = {99},
institution = {Northwestern Polytechnical University, China; Beihang University, China; Xi'an University of Technology, China, Concordia University, Canada},
abstract = {This paper presents a dual adaptive fault-tolerant control strategy for a quadrotor helicopter based on adaptive sliding mode control and adaptive boundary layer. Within the proposed adaptive control strategy, both model uncertainties and actuator faults can be compensated without the knowledge of the uncertainty bounds and fault information. By virtue of the proposed adaptive control scheme, the minimum discontinuous control gain is adopted, which significantly reduces the control chattering effect. As compared to the existing adaptive sliding mode control schemes in the literature, larger actuator faults can be tolerated by employing the proposed control scheme while suppressing control chattering. Moreover, boundary layer is used to smoothen control discontinuity and further eliminate control chattering. Nevertheless, the choice of boundary layer thickness is a trade-off between system stability and tracking accuracy. By explicitly considering this fact, an adaptive boundary layer is developed and synthesized with the proposed adaptive control framework to ensure stability and tracking accuracy of the considered system. When the control parameter tends to be overestimated, the thickness of boundary layer can be appropriately adjusted to avoid control parameter overestimation. Simulation and experimental tests of a quadrotor helicopter are both conducted to validate the effectiveness of the proposed control scheme. Its advantages are demonstrated in comparison with a conventional adaptive sliding mode control scheme. },
keywords = {Actuator fault, Adaptive sliding mode control, Fault-tolerant control, Model uncertainty, Quadrotor helicopter},
language = {English},
publisher = {Elsevier Masson}
}

This paper presents a dual adaptive fault-tolerant control strategy for a quadrotor helicopter based on adaptive sliding mode control and adaptive boundary layer. Within the proposed adaptive control strategy, both model uncertainties and actuator faults can be compensated without the knowledge of the uncertainty bounds and fault information. By virtue of the proposed adaptive control scheme, the minimum discontinuous control gain is adopted, which significantly reduces the control chattering effect. As compared to the existing adaptive sliding mode control schemes in the literature, larger actuator faults can be tolerated by employing the proposed control scheme while suppressing control chattering. Moreover, boundary layer is used to smoothen control discontinuity and further eliminate control chattering. Nevertheless, the choice of boundary layer thickness is a trade-off between system stability and tracking accuracy. By explicitly considering this fact, an adaptive boundary layer is developed and synthesized with the proposed adaptive control framework to ensure stability and tracking accuracy of the considered system. When the control parameter tends to be overestimated, the thickness of boundary layer can be appropriately adjusted to avoid control parameter overestimation. Simulation and experimental tests of a quadrotor helicopter are both conducted to validate the effectiveness of the proposed control scheme. Its advantages are demonstrated in comparison with a conventional adaptive sliding mode control scheme.

@conference{dhaybi_2020,
title = {Accurate Real-time Estimation of the Inertia Tensor of Package Delivery Quadrotors},
author = {Dhaybi, M.; Daher, N.},
booktitle = {2020 American Control Conference},
year = {2020},
institution = {American University of Beirut, Lebanon},
abstract = {The need for quadrotors to provide grasping and payload carrying abilities is ever-growing in several industries. Additional payloads attached to a quadrotor alter its dynamics and eventually affect its control system’s performance. In this work, an accurate real-time estimation of the varying mass and inertia tensor elements of a quadrotor carrying a variable payload is proposed. Parameter estimation is performed via a recursive least squares algorithm that is implemented on the quadrotor’s dynamic model using proper input-output data. Covariance resetting is integrated into the algorithm to increase the convergence rate and accuracy of the obtained estimates. The vertical motion is used to estimate the mass of the system, whereas the rotational motions around the x−, y− , and z − axes are used to identify the elements of the 3x3 inertia tensor matrix. The experiment is designed such that a persistently exciting input is generated to guarantee the convergence of the parameter estimates towards their true values. The proposed identification scheme is validated in numerical simulations and experimentation on a physical quadrotor, the Quanser QBall-2. The obtained results demonstrate the accuracy and convergence rate of the designed estimator, paving the way in front of its integration into an adaptive control system. },
issn = {0743-1619 },
keywords = {Tensile stress, Mathematical model, Estimation, Payloads, Adaptation models, Numerical models, Linear regression},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-8267-8}
}

The need for quadrotors to provide grasping and payload carrying abilities is ever-growing in several industries. Additional payloads attached to a quadrotor alter its dynamics and eventually affect its control system’s performance. In this work, an accurate real-time estimation of the varying mass and inertia tensor elements of a quadrotor carrying a variable payload is proposed. Parameter estimation is performed via a recursive least squares algorithm that is implemented on the quadrotor’s dynamic model using proper input-output data. Covariance resetting is integrated into the algorithm to increase the convergence rate and accuracy of the obtained estimates. The vertical motion is used to estimate the mass of the system, whereas the rotational motions around the x−, y− , and z − axes are used to identify the elements of the 3x3 inertia tensor matrix. The experiment is designed such that a persistently exciting input is generated to guarantee the convergence of the parameter estimates towards their true values. The proposed identification scheme is validated in numerical simulations and experimentation on a physical quadrotor, the Quanser QBall-2. The obtained results demonstrate the accuracy and convergence rate of the designed estimator, paving the way in front of its integration into an adaptive control system.

@article{wang2_2020,
title = {Active fault-tolerant control for a quadrotor helicopter against actuator faults and model uncertainties},
author = {Wang, B.; Shen, Y.; Zhang, Y.},
journal = {Aerospace Science and Technology},
year = {2020},
month = {04},
volume = {99},
institution = {Northwestern Polytechnical University, China; Concordia University, Canada},
abstract = {This paper proposes an active fault-tolerant control strategy for a quadrotor helicopter against actuator faults and model uncertainties while explicitly considering fault estimation errors based on adaptive sliding mode control and recurrent neural networks. Firstly, a novel adaptive sliding mode control is proposed. In virtue of the proposed adaptive schemes, the system tracking performance can be guaranteed in the presence of model uncertainties without stimulating control chattering. Then, due to the fact that model-based fault estimation schemes may fail to correctly estimate fault magnitudes in the presence of model uncertainties, a fault estimation scheme is proposed by designing a parallel bank of recurrent neural networks. With the trained networks, the severity of actuator faults can be precisely estimated. Finally, by synthesizing the proposed fault estimation scheme with the developed adaptive sliding mode control, an active fault-tolerant control mechanism is established. Moreover, the issue of actuator fault estimation error is explicitly considered and compensated by the proposed adaptive sliding mode control. The effectiveness of the proposed active fault-tolerant control strategy is validated through real experiments based on a quadrotor helicopter subject to actuator faults and model uncertainties. Its advantages are demonstrated in comparison with a model-based fault estimator and a conventional adaptive sliding mode control. },
keywords = {Actuator fault estimation, Active fault-tolerant control, Adaptive sliding mode control, Model uncertainties, Recurrent neural network},
language = {English},
publisher = {Elsevier Masson}
}

This paper proposes an active fault-tolerant control strategy for a quadrotor helicopter against actuator faults and model uncertainties while explicitly considering fault estimation errors based on adaptive sliding mode control and recurrent neural networks. Firstly, a novel adaptive sliding mode control is proposed. In virtue of the proposed adaptive schemes, the system tracking performance can be guaranteed in the presence of model uncertainties without stimulating control chattering. Then, due to the fact that model-based fault estimation schemes may fail to correctly estimate fault magnitudes in the presence of model uncertainties, a fault estimation scheme is proposed by designing a parallel bank of recurrent neural networks. With the trained networks, the severity of actuator faults can be precisely estimated. Finally, by synthesizing the proposed fault estimation scheme with the developed adaptive sliding mode control, an active fault-tolerant control mechanism is established. Moreover, the issue of actuator fault estimation error is explicitly considered and compensated by the proposed adaptive sliding mode control. The effectiveness of the proposed active fault-tolerant control strategy is validated through real experiments based on a quadrotor helicopter subject to actuator faults and model uncertainties. Its advantages are demonstrated in comparison with a model-based fault estimator and a conventional adaptive sliding mode control.

@conference{wang6_2020,
title = {Adaptive Fault-Tolerant Control of a Quadrotor Helicopter Based on Sliding Mode Control and Radial Basis Function Neural Network},
author = {Wang, B.; Zhang, W.; Zhang, L.; Zhang, Y.},
booktitle = {2020 International Conference on Unmanned Aircraft Systems (ICUAS)},
year = {2020},
institution = {Northwestern Polytechnical University, China; China Aeronautical Radio Electronics Research Institute, China; Concordia University, China},
abstract = {In this paper, an adaptive fault-tolerant control strategy is proposed for a quadrotor helicopter in the presence of actuator faults and model uncertainties by integrating sliding mode control and radial basis function neural network. By assuming knowledge of the bounds on external disturbances, a baseline sliding mode control is first designed to achieve the desired system tracking performance and retain insensitive to disturbances. Then, regarding actuator faults and model uncertainties of the quadrotor helicopter, neural adaptive control schemes are constructed and incorporated into the baseline sliding mode control to deal with them. Finally, a series of simulation tests are conducted to validate the effectiveness of the proposed control strategy where a quadrotor helicopter is subject to inertial moment variations and different level of actuator faults. The capability of the proposed control strategy is confirmed and verified by the demonstrated results. },
issn = {2373-6720 },
keywords = {Helicopters, Actuators, Uncertainty, Propellers, Adaptation models, Torque, Sliding mode control},
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-4279-1}
}

In this paper, an adaptive fault-tolerant control strategy is proposed for a quadrotor helicopter in the presence of actuator faults and model uncertainties by integrating sliding mode control and radial basis function neural network. By assuming knowledge of the bounds on external disturbances, a baseline sliding mode control is first designed to achieve the desired system tracking performance and retain insensitive to disturbances. Then, regarding actuator faults and model uncertainties of the quadrotor helicopter, neural adaptive control schemes are constructed and incorporated into the baseline sliding mode control to deal with them. Finally, a series of simulation tests are conducted to validate the effectiveness of the proposed control strategy where a quadrotor helicopter is subject to inertial moment variations and different level of actuator faults. The capability of the proposed control strategy is confirmed and verified by the demonstrated results.

@article{yang_2020,
title = {Adaptive Sliding Mode Fault-Tolerant Control for Uncertain Systems with Time Delay},
author = {Yang, P.; Liu, Z.; Wang, Y.; Li, D.},
journal = {International Journal of Automation Technology},
year = {2020},
volume = {14},
number = {2},
institution = {Nanjing University of Aeronautics and Astronautics, China; Chinese Flight Test Establishment, China},
abstract = {In this work, an adaptive sliding mode fault-tolerant controller is proposed for a class of uncertain systems with time delay. The integral term is added to the traditional sliding surface to improve the robustness of the control system, and then a type of special sliding surface is designed to cancel the reaching mode based on global sliding mode method. Without the need for fault detection and isolation, an adaptive law is proposed to estimate the value of actuator faults, and an adaptive sliding mode fault-tolerant controller is designed to guarantee the asymptotic stability of sliding dynamics. Finally, the presented control scheme is applied to the position control of a Qball-X4 quad-rotor UAV model to verify the effectiveness. },
issn = {1881-7629},
keywords = {fault-tolerant control, adaptive estimation, time delay, sliding mode control, uncertain systems},
language = {English},
publisher = {Fuji Technology Press}
}

In this work, an adaptive sliding mode fault-tolerant controller is proposed for a class of uncertain systems with time delay. The integral term is added to the traditional sliding surface to improve the robustness of the control system, and then a type of special sliding surface is designed to cancel the reaching mode based on global sliding mode method. Without the need for fault detection and isolation, an adaptive law is proposed to estimate the value of actuator faults, and an adaptive sliding mode fault-tolerant controller is designed to guarantee the asymptotic stability of sliding dynamics. Finally, the presented control scheme is applied to the position control of a Qball-X4 quad-rotor UAV model to verify the effectiveness.

@article{koksal_2020,
title = {Backstepping-based adaptive control of a quadrotor UAV with guaranteed tracking performance},
author = {Koksal, N.; An, H.; Fidan, B.},
journal = {ISA Transactions},
year = {2020},
institution = {University of Waterloo, Canada; Harbin Institute of Technology, China},
abstract = {In this paper, a backstepping based indirect adaptive control design and an alternative direct adaptive control scheme, both with guaranteed transient and steady-state tracking performances, are proposed for trajectory tracking of a quadrotor unmanned aerial vehicle (UAV). Backstepping techniques, combined with a prescribed performance function based error transformation, are employed in both designs to achieve the bounded transient and steady-state tracking errors of the strict-feedback position system which comprises both lateral position and altitude dynamics. The effects of parametric inertia and drag uncertainties on attitude regulation are compensated using a least squares based parameter identification algorithm in the indirect adaptive control design, and using a constructive Lyapunov analysis approach in the direct adaptive control scheme. The stability of the closed-loop system for both designs is proven via Lyapunov analysis. Simulation and experimental test results are provided to verify the effectiveness of the proposed control designs. },
keywords = {Prescribed performance bound, Backstepping control, Adaptive control, LS parameter identification, Quadrotor UAV},
language = {English},
publisher = {Elsevier Ltd.}
}

In this paper, a backstepping based indirect adaptive control design and an alternative direct adaptive control scheme, both with guaranteed transient and steady-state tracking performances, are proposed for trajectory tracking of a quadrotor unmanned aerial vehicle (UAV). Backstepping techniques, combined with a prescribed performance function based error transformation, are employed in both designs to achieve the bounded transient and steady-state tracking errors of the strict-feedback position system which comprises both lateral position and altitude dynamics. The effects of parametric inertia and drag uncertainties on attitude regulation are compensated using a least squares based parameter identification algorithm in the indirect adaptive control design, and using a constructive Lyapunov analysis approach in the direct adaptive control scheme. The stability of the closed-loop system for both designs is proven via Lyapunov analysis. Simulation and experimental test results are provided to verify the effectiveness of the proposed control designs.

@article{lopez-sanchez_2020,
title = {Experimental Parameter Identifications of a Quadrotor by Using an Optimized Trajectory},
author = {Lopez-Sanchez, I.; Montoya-Cháirez, J.; Pérez-Alcocer, R.; Moreno-Valenzuela, J.},
year = {2020},
institution = {Instituto Politécnico Nacional–CITEDI, Mexico},
abstract = {In this document, the parameter identification of a quadrotor is discussed. More precisely, the aim of this paper is to present results on the application of known methods for estimating the dynamic parameters that capture better the behavior of a quadrotor in comparison with the nominal parameters given by the manufacturer. To take into account the limitations of position, velocity, and acceleration of the quadrotor, an optimized trajectory to excite the quadrotor dynamics adequately is obtained. A proportional-integral-derivative (PID) control scheme is used to implement experimentally the tracking of the optimized trajectory. The obtained data is processed off-line to construct the standard and filtered regression models from which the parameter identification is achieved. Specifically, the least-squares and gradient descent algorithms are applied to the regression models giving four sets of estimated parameters. The four sets of parameters obtained in this work are compared with the parameters provided by the manufacturer by computing the error between simulations and experiments. In addition, the output prediction errors of the regression models are computed, thus providing another validation form. All the comparisons show that the estimated parameters are more precise than the nominal ones. The given results support the functionality of the described methodology. },
issn = {2169-3536},
keywords = {Optimized trajectory, parameter identification, quadrotor, real-time experiments, regression model},
language = {English},
publisher = {IEEE}
}

In this document, the parameter identification of a quadrotor is discussed. More precisely, the aim of this paper is to present results on the application of known methods for estimating the dynamic parameters that capture better the behavior of a quadrotor in comparison with the nominal parameters given by the manufacturer. To take into account the limitations of position, velocity, and acceleration of the quadrotor, an optimized trajectory to excite the quadrotor dynamics adequately is obtained. A proportional-integral-derivative (PID) control scheme is used to implement experimentally the tracking of the optimized trajectory. The obtained data is processed off-line to construct the standard and filtered regression models from which the parameter identification is achieved. Specifically, the least-squares and gradient descent algorithms are applied to the regression models giving four sets of estimated parameters. The four sets of parameters obtained in this work are compared with the parameters provided by the manufacturer by computing the error between simulations and experiments. In addition, the output prediction errors of the regression models are computed, thus providing another validation form. All the comparisons show that the estimated parameters are more precise than the nominal ones. The given results support the functionality of the described methodology.

@article{jardine_2020,
title = {Leveraging Data Engineering to Improve Unmanned Aerial Vehicle Control Design},
author = {Jardine, P.T.; Givigi, S.N.; Yousefi, S.},
journal = {IEEE Systems Journal},
year = {2020},
institution = {Royal Military College of Canada, Canada; Queen’s University, Canada},
abstract = {The potential benefits of big data and machine learning techniques are yet to be fully realized in real-time, safety-critical applications like unmanned aerial vehicle control. This is because of challenges related to interpretation, error susceptibility, and resources requirements. Due to their robustness and reliability, traditional model-based design techniques still dominate this landscape. However, a growing body of research in adaptive control has demonstrated the potential benefits of merging these two distinct design philosophies. This article investigates the benefits of using a combination of machine learning techniques to automatically tune parameters within a strictly defined model predictive control architecture. Fast orthogonal search and finite action-set learning automata are used to tune model coefficients and objective function weights, respectively. The strategy is validated experimentally on an actual Quanser Qball2 quadcopter and through several simulations of a Parrot AR.drone. Results demonstrate that the proposed approach improves performance while reducing design effort. },
issn = {1932-8184 },
keywords = {Model predictive control (MPC), reinforcement learning, unmanned aerial vehicles (UAVs)},
language = {English},
publisher = {IEEE}
}

The potential benefits of big data and machine learning techniques are yet to be fully realized in real-time, safety-critical applications like unmanned aerial vehicle control. This is because of challenges related to interpretation, error susceptibility, and resources requirements. Due to their robustness and reliability, traditional model-based design techniques still dominate this landscape. However, a growing body of research in adaptive control has demonstrated the potential benefits of merging these two distinct design philosophies. This article investigates the benefits of using a combination of machine learning techniques to automatically tune parameters within a strictly defined model predictive control architecture. Fast orthogonal search and finite action-set learning automata are used to tune model coefficients and objective function weights, respectively. The strategy is validated experimentally on an actual Quanser Qball2 quadcopter and through several simulations of a Parrot AR.drone. Results demonstrate that the proposed approach improves performance while reducing design effort.

@article{hu_2020,
title = {Proximal policy optimization with an integral compensator for quadrotor control},
author = {Hu, H.; Wang, Q.-L.},
journal = {Frontiers of Information Technology & Electronic Engineering},
year = {2020},
volume = {21},
number = {5},
institution = {Southeast University, China},
abstract = {We use the advanced proximal policy optimization (PPO) reinforcement learning algorithm to optimize the stochastic control strategy to achieve speed control of the “model-free” quadrotor. The model is controlled by four learned neural networks, which directly map the system states to control commands in an end-to-end style. By introducing an integral compensator into the actor-critic framework, the speed tracking accuracy and robustness have been greatly enhanced. In addition, a two-phase learning scheme which includes both offline- and online-learning is developed for practical use. A model with strong generalization ability is learned in the offline phase. Then, the flight policy of the model is continuously optimized in the online learning phase. Finally, the performances of our proposed algorithm are compared with those of the traditional PID algorithm. },
issn = {2095-9184},
keywords = {Reinforcement learning; Proximal policy optimization; Quadrotor control; Neural network},
language = {English},
publisher = {Springer-Verlag GmBH}
}

We use the advanced proximal policy optimization (PPO) reinforcement learning algorithm to optimize the stochastic control strategy to achieve speed control of the “model-free” quadrotor. The model is controlled by four learned neural networks, which directly map the system states to control commands in an end-to-end style. By introducing an integral compensator into the actor-critic framework, the speed tracking accuracy and robustness have been greatly enhanced. In addition, a two-phase learning scheme which includes both offline- and online-learning is developed for practical use. A model with strong generalization ability is learned in the offline phase. Then, the flight policy of the model is continuously optimized in the online learning phase. Finally, the performances of our proposed algorithm are compared with those of the traditional PID algorithm.

@article{yang_2020,
title = {Sliding mode prediction fault-tolerant control method for multi-delay uncertain discrete system with sensor fault},
author = {Yang, P.; Liu, Z.; Li, D.; Jiang, B.; Zhu, J.},
journal = {Transactions of the Institute of Measurement and Control},
year = {2020},
institution = {Nanjing University of Aeronautics and Astronautics, China},
abstract = {In this paper, we design a novel sliding mode prediction fault-tolerant control algorithm for multi-delays discrete uncertain systems with sensor fault. The global sliding surface is designed to replace the traditional linear sliding surface as a predictive model to ensure the global robustness of the system. For sensor fault and sliding mode buffeting, a power-dependent function reference trajectory with fault compensation is designed to attenuate chattering and achieve better stability. In the process of rolling optimization, an improved whale optimization algorithm is developed. On the premise of obtaining good convergence speed and accuracy, the optimization process can avoid falling into the local minimum value and solve the problem of premature convergence. Finally, the comparison experiments on the quad-rotor simulation platform prove the rationality and superiority of the algorithm. },
issn = {0142-3312},
keywords = {Sliding mode prediction algorithm, sensor fault, multi-delays, fault tolerant control, improved whale optimization algorithm},
language = {English},
publisher = {SAGE Publications}
}

In this paper, we design a novel sliding mode prediction fault-tolerant control algorithm for multi-delays discrete uncertain systems with sensor fault. The global sliding surface is designed to replace the traditional linear sliding surface as a predictive model to ensure the global robustness of the system. For sensor fault and sliding mode buffeting, a power-dependent function reference trajectory with fault compensation is designed to attenuate chattering and achieve better stability. In the process of rolling optimization, an improved whale optimization algorithm is developed. On the premise of obtaining good convergence speed and accuracy, the optimization process can avoid falling into the local minimum value and solve the problem of premature convergence. Finally, the comparison experiments on the quad-rotor simulation platform prove the rationality and superiority of the algorithm.

@article{perez-alcocer_2019,
title = {A novel Lyapunov-based trajectory tracking controller for a quadrotor: Experimental analysis by using two motion tasks},
author = {Perez-Alcocer, R.; Moreno-Valenzula, J.},
journal = {Mechatronics},
year = {2019},
month = {08},
volume = {61},
institution = {Instituto Politécnico Nacional-CITEDI, Mexico},
abstract = {A novel model-based controller for quadrotor trajectory tracking is presented in this paper. The closed-loop stability is studied by Lyapunov’s theory guaranteeing local asymptotical stability of the resulting equilibrium point. The performance of the proposed scheme is compared in real time with respect to three known trajectory tracking controllers having different structures. Besides, two desired trajectories encoding different motion tasks are specified. The gains of the tested controllers are selected so that the mean value of the total thrust is the same. An analysis by using different performance indexes is employed in order assess the tracking performance of each scheme. The proposed controller presents the best experimental execution for the two implemented motion tasks. },
keywords = {Quadrotor, Trajectory tracking, Model-based controller, Lyapunov theory, Real–time experiments},
language = {English},
publisher = {Elsevier Ltd.}
}

A novel model-based controller for quadrotor trajectory tracking is presented in this paper. The closed-loop stability is studied by Lyapunov’s theory guaranteeing local asymptotical stability of the resulting equilibrium point. The performance of the proposed scheme is compared in real time with respect to three known trajectory tracking controllers having different structures. Besides, two desired trajectories encoding different motion tasks are specified. The gains of the tested controllers are selected so that the mean value of the total thrust is the same. An analysis by using different performance indexes is employed in order assess the tracking performance of each scheme. The proposed controller presents the best experimental execution for the two implemented motion tasks.

@article{cajo_2019,
title = {A Survey on Fractional Order Control Techniques for Unmanned Aerial and Ground Vehicles},
author = {Cajo, R.; Mac, T.T.; Plaza, D.; Copot, C.; De Keyser, R.; Ionescu, C.},
journal = {IEEE Access},
year = {2019},
volume = {7},
institution = {Ghent University, Belgium; Hanoi University of Science and Technology, Vietnam; Escuela Superior Politécnica del Litoral, Ecuador; University of Antwerp, Belgium},
abstract = {In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade. },
issn = {2169-3536},
keywords = {Fractional calculus, fractional order control techniques, unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs)},
language = {English},
publisher = {IEEE},
pages = { 66864 - 66878}
}

In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade.

@conference{al-younes_2019,
title = {Actuator Fault-Diagnosis and Fault-Tolerant-Control using intelligent-Output-Estimator Applied on Quadrotor UAV},
author = {Al Younes, Y.; Noura, H.; Rabhi, A.; El Hajjaji, A.},
booktitle = {2019 International Conference on Unmanned Aircraft Systems (ICUAS)},
year = {2019},
institution = {Higher Colleges of Technology, UAE; Islamic University of Lebanon, Lebanon; University of Picardie, France},
abstract = {Actuator fault is a prominent system’s issue that attracts the researchers’ attentions. One type of actuator fault is a constant Loss-of-Effectiveness (LoE). In this paper, two systematic algorithms are presented. The first algorithm is designed to detect and diagnosis the actuator fault. This Fault-Detection-and-Diagnosis (FDD) approach relies on an estimator design that is called intelligent Output-Estimator (iOE). The proposed iOE is intended to improve the estimation of the actuator fault based on the Model-Free technique. The second algorithm works online after detecting, isolating and estimating the actuator fault. This Active-Fault-Tolerant-Control (AFTC) algorithm will use the estimated actuator value in a reconfigured control design to compensate for the fault. Real-time flight tests are applied on the Qball-X4 quadrotor. Different LoE actuator-fault scenarios are presented in this paper to validate the proposed algorithms. },
issn = {2373-6720},
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-0334-1},
pages = {405-412}
}

Actuator fault is a prominent system’s issue that attracts the researchers’ attentions. One type of actuator fault is a constant Loss-of-Effectiveness (LoE). In this paper, two systematic algorithms are presented. The first algorithm is designed to detect and diagnosis the actuator fault. This Fault-Detection-and-Diagnosis (FDD) approach relies on an estimator design that is called intelligent Output-Estimator (iOE). The proposed iOE is intended to improve the estimation of the actuator fault based on the Model-Free technique. The second algorithm works online after detecting, isolating and estimating the actuator fault. This Active-Fault-Tolerant-Control (AFTC) algorithm will use the estimated actuator value in a reconfigured control design to compensate for the fault. Real-time flight tests are applied on the Qball-X4 quadrotor. Different LoE actuator-fault scenarios are presented in this paper to validate the proposed algorithms.

@article{perez-alcocer_2019,
title = {Adaptive Control for Quadrotor Trajectory Tracking With Accurate Parametrization},
author = {Pérez-Alcocer, R.; Moreno-Valenzuela, J.},
journal = {IEEE Access},
year = {2019},
volume = {7},
institution = {Instituto Politécnico Nacional–CITEDI, Mexico},
abstract = {In this paper, a novel adaptive controller for quadrotor position and orientation trajectory tracking is introduced. By taking into account the coupling between the position and the orientation dynamics, an adaptive scheme based on an accurate parameterization of the model-based feedforward compensation is presented. The adaptation update laws for the adaptation parameters are designed on Lyapunov’s theory so that the stability of the state space origin of the error dynamics is guaranteed. Barbalat’s lemma ensures convergence of the tracking errors and bounding of the adaptation parameters. The extensive real-time experimental results show the practical viability of the proposed scheme. More specifically, the performance of the proposed controller is compared with an adaptive controller taken from the literature and the non-adaptive version of the proposed controller. Better results are obtained with the novel adaptive approach. },
issn = {2169-3536 },
keywords = {Adaptive control, Lyapunov-theory, quadrotor, accurate parameterization},
language = {English},
publisher = {IEEE}
}

In this paper, a novel adaptive controller for quadrotor position and orientation trajectory tracking is introduced. By taking into account the coupling between the position and the orientation dynamics, an adaptive scheme based on an accurate parameterization of the model-based feedforward compensation is presented. The adaptation update laws for the adaptation parameters are designed on Lyapunov’s theory so that the stability of the state space origin of the error dynamics is guaranteed. Barbalat’s lemma ensures convergence of the tracking errors and bounding of the adaptation parameters. The extensive real-time experimental results show the practical viability of the proposed scheme. More specifically, the performance of the proposed controller is compared with an adaptive controller taken from the literature and the non-adaptive version of the proposed controller. Better results are obtained with the novel adaptive approach.

@article{li4_2019,
title = {An Adaptive Distributed Consensus Control Algorithm Based on Continuous Terminal Sliding Model for Multiple Quad Rotors’ Formation Tracking},
author = {Li, Y.; Jiu, M.; Sun, Q.; Dong Q.},
journal = {IEEE Access},
year = {2019},
institution = {Harbin Engineering University, China},
abstract = {Distributed consensus formation tracking problem of slow convergence and low accuracy for multiple quad rotors are solved in this paper. Continuous nonsingular terminal sliding model algorithm (CNTSMA) under Inner-Outer loop control structure is considered to deal with the control problem of nonlinear, strong coupling and underactuated characteristic of a quad rotor. For better convergence and higher tracking accuracy, an adaptive algorithm (denoted by ACNTSMA) further focused on coupling of x and y directions, with sliding model observer (SMO) to compensate system disturbances and uncertainties is proposed. Furthermore, to solve the consensus formation tracking problem, a consensus control protocol under a full-connected topology based on ACNTSMA is proposed, including formation pattern consensus controller and formation distance consensus controller. Stability theory and simulation results prove the proposed control algorithm is able to accurately achieve the first-order (position and velocity) consensus for multiple quad rotors’ formation tracking. Besides, stability analysis of the proposed consensus control protocol illustrates that all sliding modes with finite-time stability applicable to second-order integral models are supposed to be established. And the proposed controller also has better convergence and faster response speed with no chattering for trajectory tracking. },
issn = {2169-3536 },
keywords = {Distributed formation tracking, consensus, continuous terminal sliding model algorithm, adaptive algorithm, multiple quad rotors, convergence},
language = {English},
publisher = {IEEE}
}

Distributed consensus formation tracking problem of slow convergence and low accuracy for multiple quad rotors are solved in this paper. Continuous nonsingular terminal sliding model algorithm (CNTSMA) under Inner-Outer loop control structure is considered to deal with the control problem of nonlinear, strong coupling and underactuated characteristic of a quad rotor. For better convergence and higher tracking accuracy, an adaptive algorithm (denoted by ACNTSMA) further focused on coupling of x and y directions, with sliding model observer (SMO) to compensate system disturbances and uncertainties is proposed. Furthermore, to solve the consensus formation tracking problem, a consensus control protocol under a full-connected topology based on ACNTSMA is proposed, including formation pattern consensus controller and formation distance consensus controller. Stability theory and simulation results prove the proposed control algorithm is able to accurately achieve the first-order (position and velocity) consensus for multiple quad rotors’ formation tracking. Besides, stability analysis of the proposed consensus control protocol illustrates that all sliding modes with finite-time stability applicable to second-order integral models are supposed to be established. And the proposed controller also has better convergence and faster response speed with no chattering for trajectory tracking.

@article{falcon_2019,
title = {An Attractive Ellipsoid-based Robust Control for Quad-Rotor Tracking},
author = {Falcon, R.; Rios, H.; Mera, M.; Dzul, A.},
journal = {IEEE Transactions on Industrial Electronics },
year = {2019},
institution = {Tecnologico Nacional de Mexico, Mexico; Instituto Politecnico Nacional, Mexico},
abstract = {This paper deals with the tracking control problem for a Quad-Rotor in the presence of external disturbances and only by means of the measurable positions and angles. To this aims, a constructive output-based robust control approach is designed based on: 1) slidingmode observation theory, for state estimation; and 2) the attractive ellipsoid method, for control design. The closedloop robust stability is proven through Lyapunov methods. The synthesis of the robust output-based control approach is expressed in terms of Linear Matrix Inequalities. Experimental results on the QBall2 platform by Quanser illustrate the feasibility of the proposed approach. },
issn = {0278-0046 },
keywords = {Robust Output-based Control, Quad-Rotor, Sliding-Mode Observers},
language = {English},
publisher = {IEEE}
}

This paper deals with the tracking control problem for a Quad-Rotor in the presence of external disturbances and only by means of the measurable positions and angles. To this aims, a constructive output-based robust control approach is designed based on: 1) slidingmode observation theory, for state estimation; and 2) the attractive ellipsoid method, for control design. The closedloop robust stability is proven through Lyapunov methods. The synthesis of the robust output-based control approach is expressed in terms of Linear Matrix Inequalities. Experimental results on the QBall2 platform by Quanser illustrate the feasibility of the proposed approach.

@article{falcon_2019,
title = {Comparative analysis of continuous sliding-modes control strategies for quad-rotor robust tracking},
author = {Falcon, R.; Rios, H.; Dzul, A.},
journal = {Control Engineering Practice},
year = {2019},
month = {09},
volume = {90},
institution = {Tecnológico Nacional de México, Mexico},
abstract = {This paper presents a comparative analysis involving four Continuous Sliding-Modes Control (Continuous-SMC) algorithms and a robustified PID control for a Quad-Rotor that can be used to deal with the tracking problem under the influence of external disturbances and uncertainties only by means of the measurable positions and angles. Such an approach is composed of a Finite-Time Sliding-Mode Observer (FT-SMO), which estimates the full state and identifies some type of disturbances, and a robust control strategy for underactuated systems. Several real-time experimental tests are carried out on the Quad-Rotor QBall2 platform by Quanser\protect \protect \relax \special {t4ht=©} under the influence of wind gusts and load disturbances. A quantitative comparison analysis is performed for all of the proposed controllers in order to illustrate their robustness properties. },
keywords = {Robust output-based control, Quad-rotor, Continuous sliding-mode control},
language = {English},
publisher = {Elsevier Ltd.},
pages = {241-256}
}

This paper presents a comparative analysis involving four Continuous Sliding-Modes Control (Continuous-SMC) algorithms and a robustified PID control for a Quad-Rotor that can be used to deal with the tracking problem under the influence of external disturbances and uncertainties only by means of the measurable positions and angles. Such an approach is composed of a Finite-Time Sliding-Mode Observer (FT-SMO), which estimates the full state and identifies some type of disturbances, and a robust control strategy for underactuated systems. Several real-time experimental tests are carried out on the Quad-Rotor QBall2 platform by Quanser\protect \protect \relax \special {t4ht=©} under the influence of wind gusts and load disturbances. A quantitative comparison analysis is performed for all of the proposed controllers in order to illustrate their robustness properties.

@conference{edhah_2019,
title = {Deep Learning Based Neural Network Controller for Quad Copter: Application to Hovering Mode},
author = {Edhah, S.; Mohamed, S.; Rehan, A.; AlDhaheri, M.; AlKhaja, A.; Zweiri, Y.},
booktitle = {2019 International Conference on Electrical and Computing Technologies and Applications (ICECTA)},
year = {2019},
institution = {Khalifa University, UAE},
abstract = {In the past few years, new advances in Deep Neural Networks (DNN) and Deep Learning (DL) has made it possible to control Rotary Unmanned Aerial Vehicles (RUAVs) with a variety of robust and intelligent techniques. In this work, a feedforward-based deep neural network is utilized to control the altitude, hovering mode, of an RUAV system. An automated search routine was developed to determine the optimum architecture of the neural network for the controller. This network was trained using the supervised learning technique, and the controller performance was compared for three different DL/DNN training paradigms; the standard feedforward method, the greedy layer-wise method, and the Long Short-Term Memory (LSTM) method in which the response of each controller was presented, where it was found that the greedy layer-wise method gives the most optimal result. },
keywords = {Deep Learning (DL), RUAV Control, Quadrotor Control, LQR, Deep Neural Network (DNN)},
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-5533-3}
}

In the past few years, new advances in Deep Neural Networks (DNN) and Deep Learning (DL) has made it possible to control Rotary Unmanned Aerial Vehicles (RUAVs) with a variety of robust and intelligent techniques. In this work, a feedforward-based deep neural network is utilized to control the altitude, hovering mode, of an RUAV system. An automated search routine was developed to determine the optimum architecture of the neural network for the controller. This network was trained using the supervised learning technique, and the controller performance was compared for three different DL/DNN training paradigms; the standard feedforward method, the greedy layer-wise method, and the Long Short-Term Memory (LSTM) method in which the response of each controller was presented, where it was found that the greedy layer-wise method gives the most optimal result.

@article{xu_2019,
title = {Observer-Based Multi-Agent System Fault Upper Bound Estimation and Fault-Tolerant Consensus Control},
author = {Xu, M.; Yang, P.; Wang, Y.; Shu, Q.},
journal = {International Journal of Innovative Computing, Information and Control},
year = {2019},
volume = {15},
number = {2},
institution = {Nanjing University of Aeronautics and Astronautics, China},
abstract = {This paper investigates the consistency of multi-agent system with actuator fault. By constructing an appropriate observer, an adaptive algorithm for the upper bound of actuator fault factor is proposed. Subsequently, a fault-tolerant control law was proposed by using the relative state information between agents and the estimated value of the fault upper bound. Moreover, by the related theory of Lyapunov, we prove the theoretical feasibility of the algorithm in realizing the consistency of multi-agent system with actuator fault and external disturbance. Finally, a numerical simulation example verifies the effectiveness of the proposed algorithm and a comparative experiment demonstrates the superiority of the proposed algorithm. },
issn = {1349-4198},
keywords = {Multi-agent system, State observer, Fault-tolerant control, Adaptive control},
language = {English},
publisher = {ICIC International},
pages = {519-534}
}

This paper investigates the consistency of multi-agent system with actuator fault. By constructing an appropriate observer, an adaptive algorithm for the upper bound of actuator fault factor is proposed. Subsequently, a fault-tolerant control law was proposed by using the relative state information between agents and the estimated value of the fault upper bound. Moreover, by the related theory of Lyapunov, we prove the theoretical feasibility of the algorithm in realizing the consistency of multi-agent system with actuator fault and external disturbance. Finally, a numerical simulation example verifies the effectiveness of the proposed algorithm and a comparative experiment demonstrates the superiority of the proposed algorithm.

@conference{steinbusch2_2019,
title = {Robust Nonlinear Output Feedback Control of a 6-DOF Quadrotor UAV},
author = {Steinbusch, A.; Reyhanoglu, M.},
booktitle = {2019 12th Asian Control Conference (ASCC)},
year = {2019},
institution = {Eindhoven University of Technology, The Netherlands; University of North Carolina at Asheville, USA},
abstract = {A robust nonlinear output feedback control method is presented, which achieves asymptotic position and attitude regulation for a six degrees of freedom (6-DOF) quadrotor unmanned aerial vehicle (UAV). The control law is designed to compensate for uncertainty in the quadrotor system dynamic model, including input-multiplicative parametric uncertainty. To reduce the computational requirement in the closed-loop system, constant feedforward estimates of the input-multiplicative uncertainty are utilized in lieu of adaptive parameter estimates. In order to avoid the high-gain feedback requirement that is characteristic of standard sliding mode observer methods, the proposed control method utilizes a bank of dynamic filters, which operates as a velocity estimator in the closed-loop system. Simulation results are provided to demonstrate the performance of the attitude control method using the Quanser 6-DOF QBall 2 system test bed. },
keywords = {Drones, Uncertainty, Mathematical model, Propellers, Dynamics, Attitude control, Observers},
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-0263-4 }
}

A robust nonlinear output feedback control method is presented, which achieves asymptotic position and attitude regulation for a six degrees of freedom (6-DOF) quadrotor unmanned aerial vehicle (UAV). The control law is designed to compensate for uncertainty in the quadrotor system dynamic model, including input-multiplicative parametric uncertainty. To reduce the computational requirement in the closed-loop system, constant feedforward estimates of the input-multiplicative uncertainty are utilized in lieu of adaptive parameter estimates. In order to avoid the high-gain feedback requirement that is characteristic of standard sliding mode observer methods, the proposed control method utilizes a bank of dynamic filters, which operates as a velocity estimator in the closed-loop system. Simulation results are provided to demonstrate the performance of the attitude control method using the Quanser 6-DOF QBall 2 system test bed.

@article{liu_2019,
title = {Sliding Mode Prediction Fault-Tolerant Control Method Based on Whale Optimization Algorithm},
author = {Liu, Z.; Yang, P.; Li, D.; Xu, M.},
journal = {International Journal of Innovative Computing, Information and Control (IJICIC)},
year = {2019},
month = {12},
volume = {15},
number = {6},
institution = {Nanjing University of Aeronautics and Astronautics, China},
abstract = {optimization algorithm is designed for fault-tolerant control of quad-rotor aircraft system with discrete time-delay uncertainties. The whole process sliding surface is used as the prediction model to ensure the global robustness, and a power function reference trajectory with fault compensation is designed to suppress the influence of chattering and suppress the uncertainty and fault. In the process of rolling optimization, considering the high-precision and fast response of the optimization process, the whale optimization algorithm is adopted, which has strong optimization performance, less parameter setting, fast convergence and high precision. The simulation shows that the algorithm has good effects in terms of robustness, weakening of chattering, and convergence speed. },
issn = {1349-4198},
keywords = {Fault tolerant control, Time varying delay, Whale optimization algorithm, Power function approach rate, Quad-rotor helicopter},
language = {English},
publisher = {ICIC International},
pages = {2119-2133}
}

optimization algorithm is designed for fault-tolerant control of quad-rotor aircraft system with discrete time-delay uncertainties. The whole process sliding surface is used as the prediction model to ensure the global robustness, and a power function reference trajectory with fault compensation is designed to suppress the influence of chattering and suppress the uncertainty and fault. In the process of rolling optimization, considering
the high-precision and fast response of the optimization process, the whale optimization algorithm is adopted, which has strong optimization performance, less parameter setting, fast convergence and high precision. The simulation shows that the algorithm has good effects in terms of robustness, weakening of chattering, and convergence speed.

@article{zhang-m_2019,
title = {Tracking Control for Unmanned Aerial Vehicles with Time-Delays Based on Event-Triggered Mechanism},
author = {Zhang, M.; Ding, Z.; Huang, J.; Huang, T.},
journal = {Journal of Control Engineering and Applied Informatics},
year = {2019},
volume = {21},
number = {3},
institution = {Shanghai Aerospace Control Technology Institute, China; University of Manchester, UK},
abstract = {A position tracking control approach is presented for quad-rotor unmanned aerial vehicles (UAVs) with multiple state time-delays and external disturbances based on an event-triggered mechanism. This approach achieves the desired performance by using less control execution, which results in a reduction in the usage rate of the onboard embedded microprocessor. First, the basic control structure is formed by a weighted multiple-model method. Next, the event-triggered mechanism is designed in such a way to achieve an aperiodic control approach. This is done by embedding the mechanism into the existing control structure. Additionally, the negative influence of time-delays and external disturbances are considered using a linear matrix inequality (LMI) technique based on a Lyapunov function. This allows the coefficients of the controller and event-triggered mechanism to be obtained. Consequently, the system can be stabilized and performs robustly. The position tracking control approach is applied to a quad-rotor UAV and the simulation results confirm its effectiveness. },
keywords = {event-triggered control; tracking control; UAV; time-delay; robust control},
language = {English}
}

A position tracking control approach is presented for quad-rotor unmanned aerial vehicles (UAVs) with multiple state time-delays and external disturbances based on an event-triggered mechanism. This approach achieves the desired performance by using less control execution, which results in a reduction in the usage rate of the onboard embedded microprocessor. First, the basic control structure is formed by a weighted multiple-model method. Next, the event-triggered mechanism is designed in such a way to achieve an aperiodic control approach. This is done by embedding the mechanism into the existing control structure. Additionally, the negative influence of time-delays and external disturbances are considered using a linear matrix inequality (LMI) technique based on a Lyapunov function. This allows the coefficients of the controller and event-triggered mechanism to be obtained. Consequently, the system can be stabilized and performs robustly. The position tracking control approach is applied to a quad-rotor UAV and the simulation results confirm its effectiveness.

@article{chen2_2019,
title = {Tracking Flight Control of Quadrotor Based on Disturbance Observer},
author = {Chen, M.; Xiong, S.; Wu, Q.},
journal = {IEEE Transactions on Systems, Man, and Cybernetics: Systems},
year = {2019},
institution = {Nanjing University of Aeronautics and Astronautics, China},
abstract = {In this paper, a tracking flight control scheme is proposed based on a disturbance observer for a quadrotor with external disturbances. To facilitate the processing of external time-varying disturbances, it is assumed to consist of some harmonic disturbances. Then, a disturbance observer is proposed to estimate the unknown disturbance. By using the output of the disturbance observer, a flight controller of the quadrotor is developed to track the given signals which are generated by the reference model. Finally, the proposed control method is applied to flight control of the quadrotor Quanser Qball 2. The experimental results are presented to demonstrate the effectiveness of the developed control strategy. },
issn = {2168-2216},
keywords = {Disturbance observer, quadrotor, tracking control},
language = {English},
publisher = {IEEE}
}

In this paper, a tracking flight control scheme is proposed based on a disturbance observer for a quadrotor with external disturbances. To facilitate the processing of external time-varying disturbances, it is assumed to consist of some harmonic disturbances. Then, a disturbance observer is proposed to estimate the unknown disturbance. By using the output of the disturbance observer, a flight controller of the quadrotor is developed to track the given signals which are generated by the reference model. Finally, the proposed control method is applied to flight control of the quadrotor Quanser Qball 2. The experimental results are presented to demonstrate the effectiveness of the developed control strategy.

@article{furtado2_2018,
title = {3-D UAV Path Planning in a Cluttered Environment using PSO},
author = {Furtado, J.S.; Liu, H.H.T.},
year = {2018},
institution = {University of Toronto Institute for Aerospace Studies, Canada},
abstract = {The use of Unmanned Aerial Vehicles (UAVs) in a wide variety of civilian and military applications such as surveillance, inspection, and precision agriculture has become increasingly popular over the last few years. The performance of the mission is based on the time taken to complete the mission. Path planning is therefore a key component in most UAV applications. The main objective of this work is to plan efficient three-dimensional (3-D) paths for a UAV to get from its start location to its goal location avoiding any collision with obstacles in the environment. Based on literature review, Swarm Intelligence (SI) based algorithm, Particle Swarm Optimisation (PSO) is utilised to generate collision free trajectories for a UAV in a cluttered environment. SI is an innovative distributed and intelligent paradigm used for solving optimization problems. It is inherently robust, scalable and stochastic, inspired by the collective behaviour seen in biological systems. The objective function being optimised is the length of the path to be own by the UAV subject to collision constraints. The algorithm generates discrete waypoints using which a smooth flyable path is generated by spline interpolation. Simulation as well as experimental results are shown to demonstrate the results of this work after testing in different scenarios. },
language = {English}
}

The use of Unmanned Aerial Vehicles (UAVs) in a wide variety of civilian and military applications such as surveillance, inspection, and precision agriculture has become increasingly popular over the last few years. The performance of the mission is based on the time taken to complete the mission. Path planning is therefore a key component in most UAV applications. The main objective of this work is to plan efficient three-dimensional (3-D) paths for a UAV to get from its start location to its goal location avoiding any collision with obstacles in the environment. Based on literature review, Swarm Intelligence (SI) based algorithm, Particle Swarm Optimisation (PSO) is utilised to generate collision free trajectories for a UAV in a cluttered environment. SI is an innovative distributed and intelligent paradigm used for solving optimization problems. It is inherently robust, scalable and stochastic, inspired by the collective behaviour seen in biological systems. The objective function being optimised is the length of the path to be own by the UAV subject to collision constraints. The algorithm generates discrete waypoints using which a smooth flyable path is generated by spline interpolation. Simulation as well as experimental results are shown to demonstrate the results of this work after testing in different scenarios.

@article{lucia_2018,
title = {A Hybrid Command Governor Scheme for Rotary Wings Unmanned Aerial Vehicles},
author = {Lucia, W.; Franze, G.; Sznaier, M.},
journal = {IEEE Transactions on Control Systems Technology},
year = {2018},
institution = {Concordia University, Canada; University of Calabria, Italy; Northeastern University, USA},
abstract = {In this paper, we develop an obstacle avoidance control scheme for autonomous aerial vehicles. The strategy is based on command governor (CG) ideas that are here extended to take into account nonconvex constraints typically arising in path planning obstacle avoidance problems. As one of its main merits, the collision avoidance task is accomplished by exploiting convex inner approximations of the obstacle-free region and an ad hoc constraints switching procedure which significantly reduces the online computations pertaining to the CG design. Experimental results on the quadrotor Qball-X4 show the applicability and effectiveness of the proposed approach. },
keywords = {Constrained control, command governor, model predictive control, obstacle avoidance, rotary wings UAV, quadro- tor QBall-X4, unmanned aerial vehicles},
language = {English},
publisher = {IEEE}
}

In this paper, we develop an obstacle avoidance control scheme for autonomous aerial vehicles. The strategy is based on command governor (CG) ideas that are here extended to take into account nonconvex constraints typically arising in path planning obstacle avoidance problems. As one of its main merits, the collision avoidance task is accomplished by exploiting convex inner approximations of the obstacle-free region and an ad hoc constraints switching procedure which significantly reduces the online computations pertaining to the CG design. Experimental results on the quadrotor Qball-X4 show the applicability and effectiveness of the proposed approach.

@article{zhou_2018,
title = {A Multi-Time-Scale Finite Time Controller for the Quadrotor UAVs with Uncertainties},
author = {Zhou, Z.; Wang, H.; Hu, Z.; Wang, Y.; Wang, H.},
journal = {Journal of Intelligent & Robotic Systems},
year = {2018},
institution = {Yanshan University, China},
abstract = {A control method with a multi-time-scale structure is proposed to perform finite time motion control of the quadrotor unmanned aerial vehicles (UAVs) with uncertainties. In order to facilitate the controller-design, finite time extended state observer (ESO) in the first and second time scales is applied to estimate the system uncertainties; the attitude controllers and the height controller are designed for finite time stabilization of the equilibriums in the third time scale; and finally, the output feedback technique is utilized to design the horizontal auxiliary controllers, meanwhile the reference angles are settled for the attitude dynamics in the fourth and slowest time scale. It allows us to analyze the system dynamics in each time scale independently, and conclusions on finite time stabilization are achieved gradually with a large region of attraction. Simulation and experimental results on the Qball2 platform are given to verify the efficacy of the strategy and establish the feasibility of implementation. },
issn = {0921-0296},
keywords = {Finite time control, Extended state observer, Multi-time-scale, System uncertainties, Quadrotor UAVs},
language = {English},
publisher = {Springer Netherlands}
}

A control method with a multi-time-scale structure is proposed to perform finite time motion control of the quadrotor unmanned aerial vehicles (UAVs) with uncertainties. In order to facilitate the controller-design, finite time extended state observer (ESO) in the first and second time scales is applied to estimate the system uncertainties; the attitude controllers and the height controller are designed for finite time stabilization of the equilibriums in the third time scale; and finally, the output feedback technique is utilized to design the horizontal auxiliary controllers, meanwhile the reference angles are settled for the attitude dynamics in the fourth and slowest time scale. It allows us to analyze the system dynamics in each time scale independently, and conclusions on finite time stabilization are achieved gradually with a large region of attraction. Simulation and experimental results on the Qball2 platform are given to verify the efficacy of the strategy and establish the feasibility of implementation.

@conference{xie_2018,
title = {A position estimation and control system for the quadrotor in GPS-deny situation based on FAST detection and optical flow},
author = {Xie, N.; Li, X.; Yu, Y.},
booktitle = {2018 33rd Youth Academic Annual Conference of Chinese Association of Automation (YAC)},
year = {2018},
institution = {University of Science and Technology Beijing, China},
abstract = {Position estimation based on vision system is essential for a UAV in the GPS-deny situation to realize the position control. However, in the practice, the hardware and software are not ideal for the UAV to carry when flying. Thus, this study is aiming at the problem of position estimation and control for a quadrotor UAV based on vision. Firstly, a position estimation algorithm based on vision is proposed, in which optical flow is used combining with FAST corner detection to ensure the real-time performance of the estimation in condition with limited loader. Meanwhile, a robust controller with nonlinear compensating input has been designed in this paper to deal with the position control for the quadrotor. A simulation is presented in this paper to verify the performance of the controller. Moreover, an experiment is also utilized in this paper to show that the method is practical and with high performance. },
keywords = {quadrotor UAV, optical flow, FAST detection, sliding model control, position estimation and control},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-7256-3 }
}

Position estimation based on vision system is essential for a UAV in the GPS-deny situation to realize the position control. However, in the practice, the hardware and software are not ideal for the UAV to carry when flying. Thus, this study is aiming at the problem of position estimation and control for a quadrotor UAV based on vision. Firstly, a position estimation algorithm based on vision is proposed, in which optical flow is used combining with FAST corner detection to ensure the real-time performance of the estimation in condition with limited loader. Meanwhile, a robust controller with nonlinear compensating input has been designed in this paper to deal with the position control for the quadrotor. A simulation is presented in this paper to verify the performance of the controller. Moreover, an experiment is also utilized in this paper to show that the method is practical and with high performance.

@article{jurado_2018,
title = {A wavelet neural control scheme for a quadrotor unmanned aerial vehicle},
author = {Jurado, F.; Lopez, S.},
journal = {Philosophical Transactions of the Royal Society of Mathematical, Physical and Engineering Sciences},
year = {2018},
volume = {376},
number = {2126},
institution = {Tecnológico Nacional de México, Mexico; Instituto Tecnológico de La Laguna, Mexico},
abstract = {Wavelets are designed to have compact support in both time and frequency, giving them the ability to represent a signal in the two-dimensional time–frequency plane. The Gaussian, the Mexican hat and the Morlet wavelets are crude wavelets that can be used only in continuous decomposition. The Morlet wavelet is complex-valued and suitable for feature extraction using the continuous wavelet transform. Continuous wavelets are favoured when high temporal and spectral resolution is required at all scales. In this paper, considering the properties from the Morlet wavelet and based on the structure of a recurrent high-order neural network model, a novel wavelet neural network structure, here called a recurrent Morlet wavelet neural network, is proposed in order to achieve a better identification of the behaviour of dynamic systems. The effectiveness of our proposal is explored through the design of a decentralized neural backstepping control scheme for a quadrotor unmanned aerial vehicle. The performance of the overall neural identification and control scheme is verified via simulation and real-time results. This article is part of the theme issue ‘Redundancy rules: the continuous wavelet transform comes of age’. },
keywords = {backstepping control, Morlet wavelet, quadrotor, recurrent wavelet neural network},
language = {English},
publisher = {The Royal Society Publishing}
}

Wavelets are designed to have compact support in both time and frequency, giving them the ability to represent a signal in the two-dimensional time–frequency plane. The Gaussian, the Mexican hat and the Morlet wavelets are crude wavelets that can be used only in continuous decomposition. The Morlet wavelet is complex-valued and suitable for feature extraction using the continuous wavelet transform. Continuous wavelets are favoured when high temporal and spectral resolution is required at all scales. In this paper, considering the properties from the Morlet wavelet and based on the structure of a recurrent high-order neural network model, a novel wavelet neural network structure, here called a recurrent Morlet wavelet neural network, is proposed in order to achieve a better identification of the behaviour of dynamic systems. The effectiveness of our proposal is explored through the design of a decentralized neural backstepping control scheme for a quadrotor unmanned aerial vehicle. The performance of the overall neural identification and control scheme is verified via simulation and real-time results.

This article is part of the theme issue ‘Redundancy rules: the continuous wavelet transform comes of age’.

@article{rios_2018,
title = {Continuous Sliding-Modes Control Strategies for Quad-Rotor Robust Tracking: Real-Time Application},
author = {Rios, H.; Falcon, R.; Gonzalez, O.A.; Dzul, A.E.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2018},
institution = {Instituto Tecnologico de La Laguna, Mexico},
abstract = {The design of robust tracking control for Quad-Rotors is an important and challenging problem nowadays. In this paper a robust tracking output-control strategy is proposed for a Quad-Rotor under the influence of external disturbances and uncertainties. Such a strategy is composed of a Finite-Time Sliding-Mode Observer (FTSMO) which estimates the full state from the measurable output and identifies some type of disturbances; and also of a combination between PID controllers and Continuous Sliding-Modes Controllers (Continuous-SMCs), that robustly track a desired time-varying trajectory with exponential convergence and despite the influence of external disturbances and uncertainties. The closed-loop stability is provided based on Input-to-State Stability (ISS) and Finite- Time ISS (FT-ISS) properties. Finally, experimental results in real-time show the performance of the proposed control strategy. },
issn = {0278-0046 },
keywords = {Robust Output-Control, Quad-Rotor, Continuous Sliding-Mode Control },
language = {English},
publisher = {IEEE}
}

The design of robust tracking control for Quad-Rotors is an important and challenging problem nowadays. In this paper a robust tracking output-control strategy is proposed for a Quad-Rotor under the influence of external disturbances and uncertainties. Such a strategy is composed of a Finite-Time Sliding-Mode Observer (FTSMO) which estimates the full state from the measurable output and identifies some type of disturbances; and also of a combination between PID controllers and Continuous Sliding-Modes Controllers (Continuous-SMCs), that robustly track a desired time-varying trajectory with exponential convergence and despite the influence of external disturbances and uncertainties. The closed-loop stability is provided based on Input-to-State Stability (ISS) and Finite- Time ISS (FT-ISS) properties. Finally, experimental results in real-time show the performance of the proposed control strategy.

@conference{kourani_2018,
title = {Coping with Quadcopter Payload Variation via Adaptive Robust Control},
author = {Kourani, A.; Kassem, K.; Daher, N.},
booktitle = {2018 IEEE International Multidisciplinary Conference on Engineering Technology (IMCET)},
year = {2018},
institution = {American University of Beirut, Lebanon; Boston University, USA},
abstract = {In this work, Adaptive Robust Control (ARC) is applied to control the motion of a quadrotor with a varying payload. ARC, based on the backstepping method, guaranties asymptotic output tracking and satisfactory transient response of the quadrotor motion in the face of uncertainties and disturbances. The control system architecture includes an outer loop where a PID controller is used to generate the position inputs, which are fed to the ARC-based attitude control system at the inner loop level. The controller design is validated against payload variation in both numerical simulation and experimentally on a quadcopter. The obtained results demonstrate the accuracy of the ARC design with a constant payload against a well-tuned fixed-gain PID controller, and the adaptation and robustness of ARC become evident when the payload is varied and tracking performance is maintained. },
keywords = {Adaptive Robust Control, quadrotor, payload change, backstepping},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-4501-7}
}

In this work, Adaptive Robust Control (ARC) is applied to control the motion of a quadrotor with a varying payload. ARC, based on the backstepping method, guaranties asymptotic output tracking and satisfactory transient response of the quadrotor motion in the face of uncertainties and disturbances. The control system architecture includes an outer loop where a PID controller is used to generate the position inputs, which are fed to the ARC-based attitude control system at the inner loop level. The controller design is validated against payload variation in both numerical simulation and experimentally on a quadcopter. The obtained results demonstrate the accuracy of the ARC design with a constant payload against a well-tuned fixed-gain PID controller, and the adaptation and robustness of ARC become evident when the payload is varied and tracking performance is maintained.

@article{mu_2018,
title = {Distributed LQR Consensus Control for Heterogeneous Multi-Agent Systems: Theory and Experiments},
author = {Mu, B.; Shi, Y.},
journal = {IEEE/ASME Transactions on Mechatronics},
year = {2018},
institution = {University of Victoria, British Columbia Canada },
abstract = {Controlling heterogeneous multi-agent systems (MASs) to cooperatively accomplish tasks is currently an emerging topic in the application-oriented research of robotics. This paper investigates the consensus problem of an MAS consisting of quadrotors and two-wheeled mobile robots (2WMRs). Directed and switching interaction topologies over the network are considered. We propose a distributed linear quadratic regulation (LQR) consensus protocol for the quadrotors and design an LQR-based Rotate&Run Consensus Scheme for the 2WMRs to update the states. We use the algebraic graph theory and stochastic matrix analysis to conduct the convergence analysis of consensus. The underactuation characteristic of the 2WMR dynamics is considered in the controller design. The effectiveness of the control methods is verified by experiments. },
issn = {1941-014X },
keywords = {Consensus, multi-agent systems, two-wheeled mobile robot, quadrotor, distributed LQR},
language = {English},
publisher = {IEEE}
}

Controlling heterogeneous multi-agent systems (MASs) to cooperatively accomplish tasks is currently an emerging topic in the application-oriented research of robotics. This paper investigates the consensus problem of an MAS consisting of quadrotors and two-wheeled mobile robots (2WMRs). Directed and switching interaction topologies over the network are considered. We propose a distributed linear quadratic regulation (LQR) consensus protocol for the quadrotors and design an LQR-based Rotate&Run Consensus Scheme for the 2WMRs to update the states. We use the algebraic graph theory and stochastic matrix analysis to conduct the convergence analysis of consensus. The underactuation characteristic of the 2WMR dynamics is considered in the controller design. The effectiveness of the control methods is verified by experiments.

@conference{nugraha_2018,
title = {Effect of alpha value change on thrust quadcopter Qball-X4 stability testing using backstepping control},
author = {Nugraha, A.T.; Anshory, I.; Rahim, R.},
booktitle = {3rd Annual Applied Science and Engineering Conference (AASEC 2018)},
year = {2018},
volume = {434},
number = {1},
institution = { Universitas Muhammadiyah Sidoarjo, Indonesia; Universiti Malaysia Perlis, Malaysia},
abstract = {Quadrotor or commonly referred to quadcopter or drone, has 4 kinds of movements. One of those movements is the impulse of the movement. In this study, a QBall-X4 quadcopter controller is using a backstepping control system to achieve movement that can reach the height when doing thrust. The results showed that the backstepping method can adjust the height and stabilize the roll angle, pitch and yaw, by adjusting alpha value (a stabilizer constant). The more precisely the alpha value of the system is more stable and the response to reach steady state is faster, with small errors. At setpoint 0 to 3 condition an error of 0.0216. },
language = {English},
series = {IOP Conf. Series: Materials Science and Engineering},
publisher = {IOP Publishing}
}

Quadrotor or commonly referred to quadcopter or drone, has 4 kinds of movements. One of those movements is the impulse of the movement. In this study, a QBall-X4 quadcopter controller is using a backstepping control system to achieve movement that can reach the height when doing thrust. The results showed that the backstepping method can adjust the height and stabilize the roll angle, pitch and yaw, by adjusting alpha value (a stabilizer constant). The more precisely the alpha value of the system is more stable and the response to reach steady state is faster, with small errors. At setpoint 0 to 3 condition an error of 0.0216.

@article{hua_2018,
title = {Fractional-order sliding mode control of uncertain QUAVs with time-varying state constraints},
author = {Hua, C.; Chen, J.; Guan, X. },
journal = {Nonlinear Dynamics},
year = {2018},
institution = {Yanshan University, China; Shanghai Jiaotong University, China},
abstract = {In this paper, a novel robust fractional-order sliding mode (FOSM)-based state constrained control scheme is designed for uncertain quadrotor UAVs (QUAVs). Model uncertainties and wind gust disturbances are taken into consideration. Under the presented framework, the overall QUAV system is decoupled into translational subsystem and rotational subsystem. These two subsystems are connected to each other through common attitude extraction algorithms. For translational subsystem, the robust state variables constrained controller is designed to ensure the position state variables within the given time-varying constraints. For the rotational subsystem, a new robust FOSM controller is constructed to track the desired attitudes with better performances. Finally, the system is proved to be asymptotically stable, and both simulation and experiment results are conducted to validate the feasibility and effectiveness of the proposed control scheme. },
issn = {0924-090X},
keywords = {Fractional-order sliding mode, State constrained control, Uncertainty, Wind gust disturbances },
language = {English},
publisher = {Springer Netherlands}
}

In this paper, a novel robust fractional-order sliding mode (FOSM)-based state constrained control scheme is designed for uncertain quadrotor UAVs (QUAVs). Model uncertainties and wind gust disturbances are taken into consideration. Under the presented framework, the overall QUAV system is decoupled into translational subsystem and rotational subsystem. These two subsystems are connected to each other through common attitude extraction algorithms. For translational subsystem, the robust state variables constrained controller is designed to ensure the position state variables within the given time-varying constraints. For the rotational subsystem, a new robust FOSM controller is constructed to track the desired attitudes with better performances. Finally, the system is proved to be asymptotically stable, and both simulation and experiment results are conducted to validate the feasibility and effectiveness of the proposed control scheme.

@article{moreno-valenzula_2018,
title = {Nonlinear PID-Type Controller for Quadrotor Trajectory Tracking},
author = {Moreno-Valenzula, J.; Perez-Alcocer, R.; Guerrero-Medina, M.; Dzul, A.},
journal = {IEEE/ASME Transactions on Mechatronics},
year = {2018},
month = {10},
volume = {23},
number = {5},
institution = {Instituto Politécnico Nacional–CITEDI, Mexico; Instituto Tecnológico de La Laguna, Mexico},
abstract = {A novel proportional-integral-derivative (PID)-type motion controller for a quadrotor is introduced in this paper. A rigorous analysis of the closed-loop system trajectories is provided, and gain tuning guidelines are discussed. Real-time experimental results consisting of the implementation of a PID-based scheme, a sliding-mode controller, and the new scheme are given. Gains are selected so that the three tested controllers present the same energy consumption. In order to assess the robustness of the controllers tested, experiments are carried out in the presence of disturbances in one of the actuators. Specifically, the disturbance consists in attenuating the force delivered. Better tracking accuracy is obtained with the introduced nonlinear PID-type algorithm. },
issn = {1083-4435},
keywords = {Disturbances, proportional-integral-de-rivative (PID)-type control, quadrotor, real-time experiments, trajectory tracking},
language = {English},
publisher = {IEEE},
pages = {2436-2447}
}

A novel proportional-integral-derivative (PID)-type motion controller for a quadrotor is introduced in this paper. A rigorous analysis of the closed-loop system trajectories is provided, and gain tuning guidelines are discussed. Real-time experimental results consisting of the implementation of a PID-based scheme, a sliding-mode controller, and the new scheme are given. Gains are selected so that the three tested controllers present the same energy consumption. In order to assess the robustness of the controllers tested, experiments are carried out in the presence of disturbances in one of the actuators. Specifically, the disturbance consists in attenuating the force delivered. Better tracking accuracy is obtained with the introduced nonlinear PID-type algorithm.

@conference{lambert2_2018,
title = {Observer-Based Sliding Mode Control of a 6-DOF Quadrotor UAV},
author = {Lambert, P.; Reyhanoglu, M.},
booktitle = {IEEE Industrial Electronics Society Conference},
year = {2018},
institution = {Eindhoven University of Technology, The Netherlands; University of North Carolina at Asheville, NC, USA},
abstract = {A sliding mode control (SMC) strategy is presented for a 6 degrees of freedom (DOF) quadrotor unmanned aerial vehicle (UAV), which achieves asymptotic position and attitude regulation. To overcome the practical limitations of velocity measurements, a sliding mode observer (SMO) is designed to estimate both the translational and rotational velocities. A rigorous Lyapunov-based analysis is provided to prove convergence to a desired set point in the presence of model uncertainties. Computer simulation results are presented, which demonstrate the effectiveness of the control law when applied to the complete nonlinear system dynamics. },
language = {English},
publisher = {IEEE}
}

A sliding mode control (SMC) strategy is presented for a 6 degrees of freedom (DOF) quadrotor unmanned aerial vehicle (UAV), which achieves asymptotic position and attitude regulation. To overcome the practical limitations of velocity measurements, a sliding mode observer (SMO) is designed to estimate both the translational and rotational velocities. A rigorous Lyapunov-based analysis is provided to prove convergence to a desired set point in the presence of model uncertainties. Computer simulation results are presented, which demonstrate the effectiveness of the control law when applied to the complete nonlinear system dynamics.

@conference{falcon_2018,
title = {Quad-Rotor Robust Tracking: A Continuous Sliding-Mode Control Strategy},
author = {Falcon, R.; Gonzzalez, O.A.; Rios, H.; Dzul, A.},
booktitle = {2018 15th International Workshop on Variable Structure Systems (VSS)},
year = {2018},
institution = {Instituto Tecnológico de La Laguna, Mexico},
abstract = {The design of robust tracking control for Quad-Rotors is an important and challenging problem nowadays. In this paper a robust tracking output-control strategy is proposed for a Quad-Rotor under the influence of external disturbances and uncertainties. Such a strategy is composed of a Finite-Time Sliding-Mode Observer (FT-SMO) which estimates the full state from the measurable output and identifies some type of disturbances; and also of a combination between PID controllers and a Continuous Sliding-Modes Controller (Continuous-SMC), that exponentially robustly track a desired time-varying trajectory and despite the influence of external disturbances and uncertainties. The closed-loop stability is provided based on Input-to-State Stability (ISS) and Finite-Time ISS (FT-ISS) properties. Finally, some experimental results in real-time show the performance of the proposed control strategy. },
issn = {2158-3986},
keywords = {Robust Output-Control, Quad-Rotor, Continuous Sliding-Mode Control},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-6440-7 }
}

The design of robust tracking control for Quad-Rotors is an important and challenging problem nowadays. In this paper a robust tracking output-control strategy is proposed for a Quad-Rotor under the influence of external disturbances and uncertainties. Such a strategy is composed of a Finite-Time Sliding-Mode Observer (FT-SMO) which estimates the full state from the measurable output and identifies some type of disturbances; and also of a combination between PID controllers and a Continuous Sliding-Modes Controller (Continuous-SMC), that exponentially robustly track a desired time-varying trajectory and despite the influence of external disturbances and uncertainties. The closed-loop stability is provided based on Input-to-State Stability (ISS) and Finite-Time ISS (FT-ISS) properties. Finally, some experimental results in real-time show the performance of the proposed control strategy.

@conference{yungaicela-naula_2018,
title = {UAV-based Air Pollutant Source Localization Using Gradient and Probabilistic Methods},
author = {Yungaicela-Naula, N.M.; Zhang, Y.; Garza-Castanon, L.E.; Minchala, L.I.},
booktitle = {2018 International Conference on Unmanned Aircraft Systems (ICUAS)},
year = {2018},
institution = {Tecnologico de Monterrey, Mexico; Concordia University, Montreal, Canada; Universidad de Cuenca, Ecuador},
abstract = {This work proposes an algorithm for air pollutant source localization using an Unmanned Aerial Vehicle (UAV). The algorithm combines a gradient-based search with a probabilistic method to localize the pollutant source. The design of the gradient-based search component is based on the simulated annealing metaheuristic and allows to trace the plume of pollutant. The probabilistic component contributes to generate a heuristic position of the source location, which is used by the gradient-based metaheuristic to navigate towards the source position, reducing the searching region at each sampling time. The proposed algorithm was tested in a simulated polluted environment. The results showed high effectiveness and robustness of the proposed strategy. },
keywords = {Path planning, environmental issues, UAS applications},
language = {English},
publisher = {IEEE}
}

This work proposes an algorithm for air pollutant source localization using an Unmanned Aerial Vehicle (UAV). The algorithm combines a gradient-based search with a probabilistic method to localize the pollutant source. The design of the gradient-based search component is based on the simulated annealing metaheuristic and allows to trace the plume of pollutant. The probabilistic component contributes to generate a heuristic position of the source location, which is used by the gradient-based metaheuristic to navigate towards the source position, reducing the searching region at each sampling time. The proposed algorithm was tested in a simulated polluted environment. The results showed high effectiveness and robustness of the proposed strategy.

@article{du_2017,
title = {A Control Performance Index for Multicopters Under Off-nominal Conditions},
author = {Du, G.-X.; Quan, Q.; Xi, Z.; Liu, Y.; Cai, K.-Y.},
year = {2017},
institution = {School of Automation Science and Electrical Engineering, Beihang University, China},
abstract = {In order to prevent loss of control (LOC) accidents, the real-time control performance monitoring (CPM) problem is studied for multicopters. Different from the existing literature, this paper does not try to monitor the performance of the controllers directly. Conversely, the unknown disturbances of the multicopter under off-nominal conditions are modeled and assessed. The monitoring results will tell the user whether a multicopter will be LOC or not. Firstly, a new degree of controllability (DoC) will be proposed for multicopters subject to control constrains and off-nominal conditions. Then a control performance index (CPI) will be defined based on the new DoC to reflect the control performance of the multicopters. Besides, the proposed CPI is applied to a new switching control framework to guide the control decision of multicopter under off-nominal conditions. Finally, simulation and experimental results will show the effectiveness of the CPI and the switching control framework proposed in this paper. },
keywords = {Multicopters, loss of control, control performance monitoring, degree of controllability},
language = {English}
}

In order to prevent loss of control (LOC) accidents, the real-time control performance monitoring (CPM) problem is studied for multicopters. Different from the existing literature, this paper does not try to monitor the performance of the controllers directly. Conversely, the unknown disturbances of the multicopter under off-nominal conditions are modeled and assessed. The monitoring results will tell the user whether a multicopter will be LOC or not. Firstly, a new degree of controllability (DoC) will be proposed for multicopters subject to control constrains and off-nominal conditions. Then a control performance index (CPI) will be defined based on the new DoC to reflect the control performance of the multicopters. Besides, the proposed CPI is applied to a new switching control framework to guide the control decision of multicopter under off-nominal conditions. Finally, simulation and experimental results will show the effectiveness of the CPI and the switching control framework proposed in this paper.

@inproceedings{wang3_2017,
title = {Adaptive Robust Control of Quadrotor Helicopter towards Payload Transportation Applications},
author = {Wang, B.; Mu, L.; Zhang, Y.},
booktitle = {Proceedings of the 36th Chinese Control Conference},
year = {2017},
institution = {Concordia University, Quebec, Canada; Northwestern Polytechnical University, Xi'an, China},
abstract = {Sliding mode control is known as a robust control approach to maintain system performance and keep it insensitive to disturbances. This paper proposes an integral sliding mode based adaptive robust control for a quadrotor helicopter with parametric uncertainties and disturbances. With the help of the synthesized on-line adaptive scheme, the uncertain parameters can be accurately estimated without the knowledge of the uncertainty bounds. In this case, there is no need to increase the discontinuous control gain, which may stimulate control chattering effect, to maintain the robustness of the controller. The effectiveness of the proposed control strategy is validated through a simulation of the payload transportation application. Compared to the commonly used linear quadratic regulator (LQR) approach, the proposed adaptive robust control strategy can maintain the tracking performance during the whole flight phase. },
issn = {1934-1768},
keywords = {Adaptive robust control, integral sliding mode, quadrotor helicopter, payload transportation},
language = {English},
publisher = {IEEE},
isbn = {978-1-5386-2918-5}
}

Sliding mode control is known as a robust control approach to maintain system performance and keep it insensitive to disturbances. This paper proposes an integral sliding mode based adaptive robust control for a quadrotor helicopter with parametric uncertainties and disturbances. With the help of the synthesized on-line adaptive scheme, the uncertain parameters can be accurately estimated without the knowledge of the uncertainty bounds. In this case, there is no need to increase the discontinuous control gain, which may stimulate control chattering effect, to maintain the robustness of the controller. The effectiveness of the proposed control strategy is validated through a simulation of the payload transportation application. Compared to the commonly used linear quadratic regulator (LQR) approach, the proposed adaptive robust control strategy can maintain the tracking performance during the whole flight phase.

@conference{wang_2017,
title = {Adaptive robust tracking control of quadrotor helicopter with parametric uncertainty and external disturbance},
author = {Wang, B.; Mu, L.; Zhang, Y.},
booktitle = {2017 International Conference on Unmanned Aircraft Systems (ICUAS)},
year = {2017},
institution = {Concordia University, Montreal, Quebec, Canada},
abstract = {This paper proposes an adaptive robust tracking control strategy for a quadrotor helicopter with parametric uncertainties and external disturbances based on sliding mode control. The inner loop of the control strategy is concerned about the attitude and altitude control of the quadrotor helicopter, while the outer loop is employed to track the desired horizontal positions. By assuming knowledge of the bounds on external disturbances, an integral sliding mode control is designed to maintain system performance and keep it insensitive to disturbances. For parametric uncertainties (e.g., total mass and moments of inertia) of the quadrotor helicopter, an on-line adaptive scheme is proposed and incorporated into the nominal sliding mode control to deal with it. With this adaptive scheme, there is no need to know the parametric uncertainty bounds. A guaranteed transient and steady-state tracking performance can be obtained with the adaptive robust sliding mode controller. The effectiveness of the proposed control strategy is validated through a simulation on a quadrotor helicopter subject to parametric uncertainties and external disturbances. },
keywords = {Helicopters, Uncertainty, Rotors, Payloads, Sliding mode control, Torque, Robustness},
language = {English},
publisher = {IEEE},
isbn = {978-1-5090-4496-2}
}

This paper proposes an adaptive robust tracking control strategy for a quadrotor helicopter with parametric uncertainties and external disturbances based on sliding mode control. The inner loop of the control strategy is concerned about the attitude and altitude control of the quadrotor helicopter, while the outer loop is employed to track the desired horizontal positions. By assuming knowledge of the bounds on external disturbances, an integral sliding mode control is designed to maintain system performance and keep it insensitive to disturbances. For parametric uncertainties (e.g., total mass and moments of inertia) of the quadrotor helicopter, an on-line adaptive scheme is proposed and incorporated into the nominal sliding mode control to deal with it. With this adaptive scheme, there is no need to know the parametric uncertainty bounds. A guaranteed transient and steady-state tracking performance can be obtained with the adaptive robust sliding mode controller. The effectiveness of the proposed control strategy is validated through a simulation on a quadrotor helicopter subject to parametric uncertainties and external disturbances.

@article{wang_2017,
title = {Adaptive Sliding Mode Fault-Tolerant Control for an Unmanned Aerial Vehicle},
author = {Wang, .; Zhang, Y.},
journal = {Unmanned Systems},
year = {2017},
volume = {5},
number = {4},
institution = {Concordia University, Canada},
abstract = {Sliding mode control (SMC) is known as a robust control method to maintain system performance and keep it insensitive to system uncertainties. To achieve this objective, the knowledge of the uncertainty bound is usually needed, but sometimes it could be a hard task. Hence, the adaptive technology is introduced to be synthesized with SMC. In this paper, a novel adaptive SMC (ASMC) scheme is proposed to accommodate system uncertainties caused by actuator faults. An integral sliding mode controller is used as the baseline controller. When actuator faults occur, there is no need to know the exact bound of the uncertainties in control effectiveness matrix. The post-fault control effectiveness matrix can be estimated by the proposed adaptive control scheme, and the control inputs will be changed accordingly. In such a way, the robustness of the controller to actuator faults is improved. With the help of adaptive change of both continuous and discontinuous control parts, a minimum value of the discontinuous control gain can be guaranteed. In this case, the resulting control effort is reduced accordingly to avoid control chattering effect. Owing to the minimized control effort to accommodate uncertainties compared to the conventional SMC, the proposed ASMC can still maintain the system performance when severer faults occur. The effectiveness of the developed algorithm is demonstrated by the simulation results based on an unmanned quadrotor helicopter under various faulty conditions. },
keywords = {Actuator fault adaptive sliding mode control, fault-tolerant control, quadrotor helicopter, unmanned aerial vehicle},
language = {English},
publisher = {World Scientific},
pages = {209-221}
}

Sliding mode control (SMC) is known as a robust control method to maintain system performance and keep it insensitive to system uncertainties. To achieve this objective, the knowledge of the uncertainty bound is usually needed, but sometimes it could be a hard task. Hence, the adaptive technology is introduced to be synthesized with SMC. In this paper, a novel adaptive SMC (ASMC) scheme is proposed to accommodate system uncertainties caused by actuator faults. An integral sliding mode controller is used as the baseline controller. When actuator faults occur, there is no need to know the exact bound of the uncertainties in control effectiveness matrix. The post-fault control effectiveness matrix can be estimated by the proposed adaptive control scheme, and the control inputs will be changed accordingly. In such a way, the robustness of the controller to actuator faults is improved. With the help of adaptive change of both continuous and discontinuous control parts, a minimum value of the discontinuous control gain can be guaranteed. In this case, the resulting control effort is reduced accordingly to avoid control chattering effect. Owing to the minimized control effort to accommodate uncertainties compared to the conventional SMC, the proposed ASMC can still maintain the system performance when severer faults occur. The effectiveness of the developed algorithm is demonstrated by the simulation results based on an unmanned quadrotor helicopter under various faulty conditions.

@conference{jardine_2017,
title = {Adaptive State-Space Model Approximation for Quadcopter using Fast Orthogonal Search},
author = {Jardine, P.T.; Givigi, S.N.; Yousefi, S.; Korenberg, M.J.},
booktitle = {2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE)},
year = {2017},
institution = {Royal Military College of Canada, ON, Canada; Queen's University, ON, Canada},
abstract = {This paper presents a novel application of Fast Orthogonal Search (FOS) to select the basis and coefficients for a linear, state-space model representing the dynamics of a quadcopter. This is developed in the context of Model Predictive Control (MPC) by evaluating the performance of the approximate model over finite prediction horizons in different flight regimes. A time-varying model is implemented using sliding window (SW-FOS) and recursive (R-FOS) techniques. FOS was selected because it provides a numerically efficient technique for selecting which basis terms are important in the model while simultaneously solving for their coefficients. Based on experimental data from an actual quadcopter, SWFOS provided mean squared error performance similar to Least Squares (LS) while requiring on average 5 fewer states in the state-space model. R-FOS produced more accurate results with significantly reduced computation times. Both SW-FOS and R-FOS provided linear, time-varying models that adapted to various flight regimes. },
keywords = {Computational modeling, State-space methods, Nonlinear dynamical systems, Computers, Numerical models, Adaptation models},
language = {English},
publisher = {IEEE},
isbn = {978-1-5090-5539-5},
pages = {465-470}
}

This paper presents a novel application of Fast Orthogonal Search (FOS) to select the basis and coefficients for a linear, state-space model representing the dynamics of a quadcopter. This is developed in the context of Model Predictive Control (MPC) by evaluating the performance of the approximate model over finite prediction horizons in different flight regimes. A time-varying model is implemented using sliding window (SW-FOS) and recursive (R-FOS) techniques. FOS was selected because it provides a numerically efficient technique for selecting which basis terms are important in the model while simultaneously solving for their coefficients. Based on experimental data from an actual quadcopter, SWFOS provided mean squared error performance similar to Least Squares (LS) while requiring on average 5 fewer states in the state-space model. R-FOS produced more accurate results with significantly reduced computation times. Both SW-FOS and R-FOS provided linear, time-varying models that adapted to various flight regimes.

@article{wang_2017,
title = {An Adaptive Fault-Tolerant Sliding Mode Control Allocation Scheme for Multirotor Helicopter Subject to Simultaneous Actuator Faults},
author = {Wang, B.; Zhang, Y.},
journal = {IEEE Transactions on Industrial Electronics},
year = {2017},
institution = {Concordia University, Canada},
abstract = {This paper proposes a novel adaptive sliding mode based control allocation scheme for accommodating simultaneous actuator faults. The proposed control scheme includes two separate control modules with virtual control part and control allocation part, respectively. As a lowlevel control module, the control allocation/re-allocation scheme is used to distribute/redistribute virtual control signals among the available actuators under fault-free or faulty cases, respectively. In the case of simultaneous actuator faults, the control allocation and re-allocation module may fail to meet the required virtual control signal which will degrade the overall system stability. The proposed online adaptive scheme can seamlessly adjust the control gains for the high-level sliding mode control module and reconfigure the distribution of control signals to eliminate the effect of the virtual control error and maintain stability of the closed-loop system. In addition, with the help of the boundary layer for constructing the adaptation law, the overestimation of control gains is avoided, and the adaptation ceases once the sliding variable is within the boundary layer. A significant feature of this study is that the stability of the closed-loop system is guaranteed theoretically in the presence of simultaneous actuator faults. The effectiveness of the proposed control scheme is demonstrated by experimental results based on a modified unmanned multirotor helicopter under both single and simultaneous actuator faults conditions with comparison to a conventional sliding mode controller and a linear quadratic regulator scheme. },
issn = {0278-0046 },
keywords = {Adaptive sliding mode control, control allocation/re-allocation, fault-tolerant control, hardware redundancy, multirotor helicopter, simultaneous actuator faults},
language = {English},
publisher = {IEEE}
}

This paper proposes a novel adaptive sliding mode based control allocation scheme for accommodating simultaneous actuator faults. The proposed control scheme includes two separate control modules with virtual control part and control allocation part, respectively. As a lowlevel control module, the control allocation/re-allocation scheme is used to distribute/redistribute virtual control signals among the available actuators under fault-free or faulty cases, respectively. In the case of simultaneous actuator faults, the control allocation and re-allocation module may fail to meet the required virtual control signal which will degrade the overall system stability. The proposed online adaptive scheme can seamlessly adjust the control gains for the high-level sliding mode control module and reconfigure the distribution of control signals to eliminate the effect of the virtual control error and maintain stability of the closed-loop system. In addition, with the help of the boundary layer for constructing the adaptation law, the overestimation of control gains is avoided, and the adaptation ceases once the sliding variable is within the boundary layer. A significant feature of this study is that the stability of the closed-loop system is guaranteed theoretically in the presence of simultaneous actuator faults. The effectiveness of the proposed control scheme is demonstrated by experimental results based on a modified unmanned multirotor helicopter under both single and simultaneous actuator faults conditions with comparison to a conventional sliding mode controller and a linear quadratic regulator scheme.

In order to solve the trajectory tracking of a quadrotor called QBall2 which is produced by Quanser Company of Canada, an integral backstepping controller is designed. A nonlinear mathematical model of QBall2 in the presence of external disturbances is obtained and a MATLAB/Simulink simulation system is built to validate the nonlinear trajectory tracking controller and compare the difference of PID and integral backstepping. The simulation results illustrate the good tracking performances of the designed nonlinear trajectory tracking controller.

@conference{jardine2_2017,
title = {Experimental results for autonomous model-predictive trajectory planning tuned with machine learning},
author = {{Jardine, P.T.; Givigi, S.N.; Yousefi, S.},
booktitle = {2017 Annual IEEE International Systems Conference (SysCon)},
year = {2017},
institution = {Royal Military College of Canada, ON, Canada; Queen's University, ON, Canada},
abstract = {This paper presents experimental results of a high-level trajectory planning algorithm for autonomous quadrotors based on Model Predictive Control (MPC) tuned with machine learning. Time-varying planar inequality constraints are used to avoid obstacles. The nonlinear plant dynamics are linearized around a hover condition. Learning Automata is used to select the relative weights of the objective function and compensate for nonlinearities lost during this linearization. The proposed technique successfully guides a quadcopter to a target while avoiding a spherical obstacle placed in its path. These results demonstrate the potential application for MPC-based techniques in unmanned aerial vehicle operations that involve obstacles. Furthermore, they demonstrate that machine learning can be used to tune parameters in an MPC formulation.This paper presents experimental results of a high-level trajectory planning algorithm for autonomous quadrotors based on Model Predictive Control (MPC) tuned with machine learning. Time-varying planar inequality constraints are used to avoid obstacles. The nonlinear plant dynamics are linearized around a hover condition. Learning Automata is used to select the relative weights of the objective function and compensate for nonlinearities lost during this linearization. The proposed technique successfully guides a quadcopter to a target while avoiding a spherical obstacle placed in its path. These results demonstrate the potential application for MPC-based techniques in unmanned aerial vehicle operations that involve obstacles. Furthermore, they demonstrate that machine learning can be used to tune parameters in an MPC formulation. },
issn = {2472-9647},
keywords = {Trajectory, Planning, Iron, Linear programming, Computational modeling, Nonlinear dynamical systems, Unmanned aerial vehicles},
language = {English},
publisher = {IEEE}
}

This paper presents experimental results of a high-level trajectory planning algorithm for autonomous quadrotors based on Model Predictive Control (MPC) tuned with machine learning. Time-varying planar inequality constraints are used to avoid obstacles. The nonlinear plant dynamics are linearized around a hover condition. Learning Automata is used to select the relative weights of the objective function and compensate for nonlinearities lost during this linearization. The proposed technique successfully guides a quadcopter to a target while avoiding a spherical obstacle placed in its path. These results demonstrate the potential application for MPC-based techniques in unmanned aerial vehicle operations that involve obstacles. Furthermore, they demonstrate that machine learning can be used to tune parameters in an MPC formulation.This paper presents experimental results of a high-level trajectory planning algorithm for autonomous quadrotors based on Model Predictive Control (MPC) tuned with machine learning. Time-varying planar inequality constraints are used to avoid obstacles. The nonlinear plant dynamics are linearized around a hover condition. Learning Automata is used to select the relative weights of the objective function and compensate for nonlinearities lost during this linearization. The proposed technique successfully guides a quadcopter to a target while avoiding a spherical obstacle placed in its path. These results demonstrate the potential application for MPC-based techniques in unmanned aerial vehicle operations that involve obstacles. Furthermore, they demonstrate that machine learning can be used to tune parameters in an MPC formulation.