Continuous-time dynamic solvers have emerged as a viable alternative for online optimization of model predictive control (MPC). This class of solvers emulates the behavior of MPC by tracing its solution trajectories to the Karush-Kuhn-Tucker (KKT) optimality point. In this paper, we develop an analog circuit architecture for the hardware realization of such dynamic controllers. Using the gradient dynamics as a case study, we develop a prototype solver using a Field Programmable Analog Array (FPAA) and we validate its efficacy on a quadruple water tank system.

We provide a comprehensive review and practical implementation of a recently developed model predictive control (MPC) framework for controlling unknown systems using only measured data and no explicit model knowledge. Our approach relies on an implicit system parametrization from behavioral systems theory based on one measured input-output trajectory. The presented MPC schemes guarantee closed-loop stability for unknown linear time-invariant (LTI) systems, even if the data are affected by noise. Further, we extend this MPC framework to control unknown nonlinear systems by continuously updating the data-driven system representation using new measurements. The simple and intuitive applicability of our approach is demonstrated with a nonlinear four-tank system in simulation and in an experiment.

This paper presents the mathematical design and implementation of a robust H2 output feedback controller for the vertical nonlinear coupled-tank system. Considering the growth of the complicated chemical processes in industries in the last decades, the necessity for the controllers with high robustness and proficiency is demanded. Therefore, to overcome some deficiencies of classical controllers such as proportional integral (PI), the robust H2 output feedback controller is proposed to control the liquid level of the coupled tank system benchmark. Because of the nonlinearity of the system and the interactions between two tanks, the behavior of the controller in terms of the performance and disturbance rejection is on the main scene. The linear matrix inequalities (LMI) is used to derive the design procedure. The effectiveness of the proposed approach in the setpoint tracking is highlighted in comparison with the PI plus feedforward controller and the acceptable results are achieved.

In this thesis, the problem of fault detection in an interconnected water tank system using a particle filter is investigated. The objective of the work is to use the particle filter to detect the time of leakage faults occurring in an interconnected water tank system. A physical three tank system is built using commercial off the shelf components. Water flows into the system from a sump via two pumps, and flows between the tanks through linking tubes at the bottom of each tank. Leakage faults can be induced by opening a leakage tube at the bottom of a tank. A mathematical model is built to capture the dynamics of normal and faulty behaviour. The height of water in each tank is measured using pressure sensors. The Particle filter compares water height measurements to model predictions to determine if the system is operating normally or if a fault has occurred. The particle filter can correctly detect the time of one or two fault occurrences in the system at most 8 seconds after a fault occurs. Also, this thesis investigates the effect that time delayed measurement data and incipient leakage fault have on the fault detection performance of the particle filter.

@article{shendge_2020,
title = {Disturbance observer based controller under noisy measurement for tracking of nDOF uncertain mismatched nonlinear},
author = {Chaudhari, S.; Shendge, P.D.; Phadke, S.B.},
journal = {IEEE/ASME Transactions on Mechatronics},
year = {2020},
institution = {College of Engineering Pune, India},
abstract = {This paper analyzes a recent result on tracking control of nonlinear, mismatched interconnected systems and points out its drawback with regard to noise amplification that originates from numerical differentiation of tracking error. One of the objectives of the paper is to propose two remedial measures and show their improvements by analysis for performance and stability. In the first remedy, the derivative of the tracking error is obtained without recourse to numerical differentiation while the second remedy offers a solution that does not need the derivative of the tracking error. Another objective of the paper is to propose an extension to decentralized sliding mode control of interconnected systems. Unlike other published results, the extension can assure local sliding in each subsystem. The proposed remedies are validated by numerical simulation, and experimentation on a laboratory coupled tank system. A discussion with a generalized extended state observer (GESO) based method and comparative simulations with other well known methods are carried out. },
keywords = {disturbance observer, sliding mode control, measurement noise, mismatched nonlinear systems, decentralized control},
language = {English},
publisher = {IEEE}
}

This paper analyzes a recent result on tracking control of nonlinear, mismatched interconnected systems and points out its drawback with regard to noise amplification that originates from numerical differentiation of tracking error. One of the objectives of the paper is to propose two remedial measures and show their improvements by analysis for performance and stability. In the first remedy, the derivative of the tracking error is obtained without recourse to numerical differentiation while the second remedy offers a solution that does not need the derivative of the tracking error. Another objective of the paper is to propose an extension to decentralized sliding mode control of interconnected systems. Unlike other published results, the extension can assure local sliding in each subsystem. The proposed remedies are validated by numerical simulation, and experimentation on a laboratory coupled tank system. A discussion with a generalized extended state observer (GESO) based method and comparative simulations with other well known methods are carried out.

A real-time implementation of a digital proportional-integral controller on a Cyber-Physical Systems (CPS) node for a coupled-tank plant to provide a testbed for verification of control algorithm and communication is described. The CPS node embedded computer is based on the ADuC841 8-bit microcontroller and the embedded real-time multitasking software was written in Pascal language. The node is interfaced to the Quanser’s coupled-tank plant via the on-chip 12-bit analog-to-digital and digital-to-analog converters, and a RS-485 communication network connects it to other nodes to form a CPS. Experimental results on the closed-loop control performances of the digital proportional-integral controller with three different tuning sets on the coupled-tank plant, verified the functionality of the digital control algorithm.

@conference{de-keyser2_2019,
title = {Experimental Validation of an Efficient Disturbance Rejection Method for Dead-Time Processes using Internal Model Control},
author = {De Keyser, R.; Muresan, C.I.},
booktitle = {2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)},
year = {2019},
institution = {Ghent University, Belgium; Technical University of Cluj-Napoca, Romania},
abstract = {When controlling industrial processes, setpoint tracking and disturbance rejection play an important part in the design and tuning of the PID controller parameters, especially since most of these processes exhibit dead-times. Internal Model Control (IMC) algorithms have proven to be quite efficient in setpoint tracking issues. However, the basic tuning rules for IMC lead to PID controllers that cause a sluggish disturbance rejection, especially for delay dominant processes (i.e. with big ratio of dead-time versus the process time constant). In the current paper, the experimental validation of a novel idea for tuning IMC controllers for improved disturbance rejection is presented. The method is based on using a disturbance filter that compensates for the dead-time, provided that the process is affected by stochastic disturbances having their spectral energy in a narrow frequency band (such as quasi-periodic disturbances). Diophantine equations are used to compute the disturbance filter coefficients. The exaperimental case study consists in the Quanser six tanks process. },
issn = {1946-0740},
keywords = {component, IMC, Disturbance rejection, Dead-time processes, experimental validation},
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-0304-4}
}

When controlling industrial processes, setpoint tracking and disturbance rejection play an important part in the design and tuning of the PID controller parameters, especially since most of these processes exhibit dead-times. Internal Model Control (IMC) algorithms have proven to be quite efficient in setpoint tracking issues. However, the basic tuning rules for IMC lead to PID controllers that cause a sluggish disturbance rejection, especially for delay dominant processes (i.e. with big ratio of dead-time versus the process time constant). In the current paper, the experimental validation of a novel idea for tuning IMC controllers for improved disturbance rejection is presented. The method is based on using a disturbance filter that compensates for the dead-time, provided that the process is affected by stochastic disturbances having their spectral energy in a narrow frequency band (such as quasi-periodic disturbances). Diophantine equations are used to compute the disturbance filter coefficients. The exaperimental case study consists in the Quanser six tanks process.

@article{stohy_2019,
title = {Parameter Estimation and PI Control for a Water Coupled Tank System},
author = {Stohy, M.G.; Abbas, H.S.; El-Sayed, A.-H.M.; Abo El-Maged A.G.},
journal = {Journal of Advanced Engineering Trends},
year = {2019},
volume = {38},
number = {2},
institution = {Minia University, Egypt; Assiut University, Egypt; El Minia High Institute for Engineering and Technology, Egypt},
abstract = {This paper presents an experimental application of parameter estimation and PI controller design for a state-coupled two-tank liquid level system. For this plant it is desired to provide a satisfactory performance for the control system. In the proposed approach a genetic algorithm optimization method is used to estimate the plant physical parameter values of the nonlinear system. The GA has been provided the system parameters as well as the real system performance is achieved. Then, a proportional-integral controller is designed to control the plant based on the linearized model and implemented experimentally. The experimental implementation provides a good performance and response. },
keywords = {Parameter Estimation, Genetic Algorithm, Proportional Integral Control, Coupled Tanks System},
language = {English},
publisher = {NotionWaveInc.},
pages = {147-159}
}

This paper presents an experimental application of parameter estimation and PI controller design for a state-coupled two-tank liquid level system. For this plant it is desired to provide a satisfactory performance for the control system. In the proposed approach a genetic algorithm optimization method is used to estimate the plant physical parameter values of the nonlinear system. The GA has been provided the system parameters as well as the real system performance is achieved. Then, a proportional-integral controller is designed to control the plant based on the linearized model and implemented experimentally. The experimental implementation provides a good performance and response.

@conference{goyal_2019,
title = {R∞ Based PI Controller Design for Coupled Tank System through Polytopic Modeling},
author = {Goyal, J.K.; Aggarwal, S.; Ghosh, S.; Kamal, S.; Vuyyuru, U. },
booktitle = {IECON 2019 - 45th Annual Conference of the IEEE Industrial Electronics Society},
year = {2019},
institution = {Indian Institute of Technology Varanasi, India; Indian Institute of Technology Kharagpur, India},
abstract = {This paper addresses a new technique to cater to the nonlinear dynamics involved in a coupled tank system. Earlier approaches to designing a linear controller for a nonlinear system are two-fold. The first considers linearizing the plant around some operating point, thereby ignoring the dynamics posed by higher-order terms while the second approach is to represent the system nonlinearities in the form of model uncertainties, without any approximation of the higher order terms. The latter method forms the basis of design considered in this paper. The nonlinear model of a coupled tank system is represented in the form of a polytopic system that allows for the implementation of a linear controller. The variation in nonlinear term is treated as an uncertain parameter for the system representation. A R∞ based Proportional Integral (PI) controller is designed combined with pole placement in a desired Linear Matrix Inequality (LMI) region to ensure better transient behavior of the system. Experimental results have been provided and compared with conventional design to illustrate the efficacy of the proposed design method. },
issn = {2577-1647},
keywords = {Coupled Tank System, H∞ controller, Linear matrix inequalities, Proportional-Integral controller, Polytopic modeling},
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-4878-6}
}

This paper addresses a new technique to cater to the nonlinear dynamics involved in a coupled tank system. Earlier approaches to designing a linear controller for a nonlinear system are two-fold. The first considers linearizing the plant around some operating point, thereby ignoring the dynamics posed by higher-order terms while the second approach is to represent the system nonlinearities in the form of model uncertainties, without any approximation of the higher order terms. The latter method forms the basis of design considered in this paper. The nonlinear model of a coupled tank system is represented in the form of a polytopic system that allows for the implementation of a linear controller. The variation in nonlinear term is treated as an uncertain parameter for the system representation. A R∞ based Proportional Integral (PI) controller is designed combined with pole placement in a desired Linear Matrix Inequality (LMI) region to ensure better transient behavior of the system. Experimental results have been provided and compared with conventional design to illustrate the efficacy of the proposed design method.

@conference{de-keyser_2019,
title = {Robust Estimation of a SOPDT Model from Highly Corrupted Step Response Data},
author = {De keyser, R.; Muresan, C.I.},
booktitle = {2019 18th European Control Conference (ECC)},
year = {2019},
institution = {Ghent University, Belgium; Technical University of Cluj-Napoca, Romania},
abstract = {Most industrial processes, even though complex in nature, can be represented using second order plus dead-time models, usually determined from step response data, which capture the essential process dynamics. The parameters of these models are computed based on specific algorithms. However, the great majority of these algorithms require system identification basic knowledge and are thus difficult to be used by the process engineer. The focus of this paper is to introduce a new method for computing the parameters of such models. The major advantage over existing methods is that it does not require any system identification expertise, being fully automatic. Additional advantages include robustness to noise, disturbances and system order. All of these are emphasized through several numerical examples, as well as an experimental validation. },
language = {English},
publisher = {IEEE},
isbn = {978-1-7281-1314-2 }
}

Most industrial processes, even though complex in nature, can be represented using second order plus dead-time models, usually determined from step response data, which capture the essential process dynamics. The parameters of these models are computed based on specific algorithms. However, the great majority of these algorithms require system identification basic knowledge and are thus difficult to be used by the process engineer. The focus of this paper is to introduce a new method for computing the parameters of such models. The major advantage over existing methods is that it does not require any system identification expertise, being fully automatic. Additional advantages include robustness to noise, disturbances and system order. All of these are emphasized
through several numerical examples, as well as an experimental validation.

Plant-wide control implies advanced supervisory algorithms to maintain desired performance in the involved coupled sub-systems. The dynamical interactions among these sub-systems can vary with the operating point, material properties and disturbances present in the process. Recirculating loops introduce additional phenomena in the dynamic response, further challenging the control tasks. Complex process dynamics may be linear parameter varying (LPV) and may be difficult, if not impossible, to identify properly. In this context, maintaining global performance is a challenge one must undertake with limited information at hand. This paper investigates the trade-off between the complexity of the implementation and achieved performance, using supervisory predictive control with limited information shared, applied on a test-bench representative for process control industry. The robustness of the proposed algorithms is tested against a nominal scenario in which the prediction model is fully identified, with complete information exchange. Experimental tests are performed on a test-bench process characterized by strong interactions, and the results illustrate the usefulness of this work.

@article{nandi_2018,
title = {Chance Constraint based Design of Open-Loop Controllers for Linear Uncertain Systems},
author = {Nandi, S.; Singh, T.},
journal = { IEEE/ASME Transactions on Mechatronics},
year = {2018},
institution = {University at Buffalo, USA},
abstract = {This paper considers the problem of state-to-state transition with state and control constraints, for a linear system with time invariant model parameter uncertainties. Polynomial chaos is used to transform the stochastic model to a deterministic surrogate model. This surrogate model is used to pose a chance constrained optimal control problem where the state constraints and the residual energy cost are represented in terms of the mean and variance of the stochastic states. The resulting convex optimization is illustrated on the problem of rest-to-rest maneuver of the benchmark floating oscillator and on an experimental two-tank setup. },
issn = {1083-4435 },
keywords = {Uncertain System, Vibration Control, Chance Constraint, Polynomial Chaos, Stochastic Optimal Control},
language = {English},
publisher = {IEEE}
}

This paper considers the problem of state-to-state transition with state and control constraints, for a linear system with time invariant model parameter uncertainties. Polynomial chaos is used to transform the stochastic model to a deterministic surrogate model. This surrogate model is used to pose a chance constrained optimal control problem where the state constraints and the residual energy cost are represented in terms of the mean and variance of the stochastic states. The resulting convex optimization is illustrated on the problem of rest-to-rest maneuver of the benchmark floating oscillator and on an experimental two-tank setup.

@article{dai_2018,
title = {Uncertainty and Disturbance Estimator-Based Backstepping Control for Nonlinear Systems With Mismatched Uncertainties and Disturbances},
author = {Dai, J.; Ren, B.; Zhong, Q.-C. },
journal = {Journal of Dynamic Systems, Measurement, and Control},
year = {2018},
volume = {140},
number = {12},
institution = {Texas Tech University, USA; Illinois Institute of Technology, USA},
abstract = {This paper proposes an uncertainty and disturbance estimator (UDE)-based controller for nonlinear systems with mismatched uncertainties and disturbances, integrating the UDE-based control and the conventional backstepping scheme. The adoption of the backstepping scheme helps to relax the structural constraint of the UDE-based control. Moreover, the reference model design in the UDE-based control offers a solution to address the “complexity explosion” problem of the backstepping approach. Furthermore, the strict-feedback form condition in the conventional backstepping approach is also relaxed by using the UDE-based control to estimate and compensate “disturbance-like” terms including nonstrict-feedback terms and intermediate system errors. The uniformly ultimate boundedness of the closed-loop system is analyzed. Both numerical and experimental studies are provided. },
keywords = {uncertainty and disturbance estimator, backstepping, mismatched uncertainties and disturbances},
language = {English},
publisher = {ASME}
}

This paper proposes an uncertainty and disturbance estimator (UDE)-based controller for nonlinear systems with mismatched uncertainties and disturbances, integrating the UDE-based control and the conventional backstepping scheme. The adoption of the backstepping scheme helps to relax the structural constraint of the UDE-based control. Moreover, the reference model design in the UDE-based control offers a solution to address the “complexity explosion” problem of the backstepping approach. Furthermore, the strict-feedback form condition in the conventional backstepping approach is also relaxed by using the UDE-based control to estimate and compensate “disturbance-like” terms including nonstrict-feedback terms and intermediate system errors. The uniformly ultimate boundedness of the closed-loop system is analyzed. Both numerical and experimental studies are provided.

@conference{de-lima-souza_2017,
title = {Development of the Software for Identification of Nonlinear Dynamic Systems Using the Modified Fuzzy Wavelet Neural Network},
author = {de Lima Souza, F.R.; da Costa Martins, J.K.E.; de Araujo, F.M.U.},
booktitle = {13th Brazilian Symposium on Intelligent Automation (SBAI)},
year = {2017},
institution = {Federal University of Rio Grande do Norte, Brazil},
abstract = {In this paper, a software was developed to identify nonlinear dynamical systems with time delay using the modified Fuzzy Wavelet Neural Network technique. To evaluate both the technique and the software developed a Quanser coupled tanks system was identified. In the identification process was seen that the software is simple and easy to use. The result show the validation the software and the technique. },
keywords = {System Identification, Artificial Neural Networks, Modified Fuzzy Wavelet Neural Networks},
language = {Portuguese}
}

In this paper, a software was developed to identify nonlinear dynamical systems with time delay using the modified Fuzzy Wavelet Neural Network technique. To evaluate both the technique and the software developed a Quanser coupled tanks system was identified. In the identification process was seen that the software is simple and easy to use. The result show the validation the software and the technique.

@article{arun_2017,
title = {Modeling, stability analysis, and computational aspects of some simplest nonlinear fuzzy two-term controllers derived via center of area/gravity defuzzification},
author = {Arun, N.K.; Mohan, B.M.},
journal = {ISA Transactions},
year = {2017},
institution = {Department of Electrical Engineering, Indian Institute of Technology, Kharagpur, India},
abstract = {The mathematical models reported in the literature so far have been found using Center of Sums (CoS) defuzzification method only. It appears that no one has found models using Center of Area (CoA) or Center of Gravity (CoG) defuzzification method. Although there have been some works reported to deal with modeling of fuzzy controllers via Centroid method, all of them have in fact used CoS method only. In this paper, for the first time mathematical models of the simplest Mamdani type fuzzy Proportional Integral (PI)/Proportional Derivative (PD) controllers via CoG defuzzification are presented. L-type and G-type membership functions over different Universes of Discourse (UoDs) are considered for the input variables. L-type, ?-type and G-type membership functions are considered for the output variable. Three linear fuzzy control rules relating all four input fuzzy sets to three output fuzzy sets are chosen. Two triangular norms namely Algebraic Product (AP) and Minimum (Min), Maximum (Max) triangular co-norm, and two inference methods, Larsen Product (LP) and Mamdani Minimum (MM), are used. Properties of the models are studied. Stability analysis of closed-loop systems containing one of these controller models in the loop is done using the Small Gain theorem. Since digital controllers are implemented using digital processors, computational and memory requirements of these fuzzy controllers and conventional (nonfuzzy) controllers are compared. A rough estimate of the computational time taken by the digital computer while implementing any of these discrete-time fuzzy controllers is given. Two nonlinear plants are considered to show the superiority of the simplest fuzzy controller obtained using CoA or CoG defuzzification method over the simplest fuzzy controller obtained using CoS method and reported recently. Real-time implementation of one of the developed controller models is done on coupled tank experimental setup to show the feasibility of the developed model. },
keywords = {Center of gravity/area defuzzification; Mathematical modeling; Stability analysis; Computational aspects; PI/PD control; Nonlinear control; Fuzzy control; Mamdani type controller},
language = {English},
publisher = {Elsevier Ltd.}
}

The mathematical models reported in the literature so far have been found using Center of Sums (CoS) defuzzification method only. It appears that no one has found models using Center of Area (CoA) or Center of Gravity (CoG) defuzzification method. Although there have been some works reported to deal with modeling of fuzzy controllers via Centroid method, all of them have in fact used CoS method only. In this paper, for the first time mathematical models of the simplest Mamdani type fuzzy Proportional Integral (PI)/Proportional Derivative (PD) controllers via CoG defuzzification are presented. L-type and G-type membership functions over different Universes of Discourse (UoDs) are considered for the input variables. L-type, ?-type and G-type membership functions are considered for the output variable. Three linear fuzzy control rules relating all four input fuzzy sets to three output fuzzy sets are chosen. Two triangular norms namely Algebraic Product (AP) and Minimum (Min), Maximum (Max) triangular co-norm, and two inference methods, Larsen Product (LP) and Mamdani Minimum (MM), are used. Properties of the models are studied. Stability analysis of closed-loop systems containing one of these controller models in the loop is done using the Small Gain theorem. Since digital controllers are implemented using digital processors, computational and memory requirements of these fuzzy controllers and conventional (nonfuzzy) controllers are compared. A rough estimate of the computational time taken by the digital computer while implementing any of these discrete-time fuzzy controllers is given. Two nonlinear plants are considered to show the superiority of the simplest fuzzy controller obtained using CoA or CoG defuzzification method over the simplest fuzzy controller obtained using CoS method and reported recently. Real-time implementation of one of the developed controller models is done on coupled tank experimental setup to show the feasibility of the developed model.

@article{bertelli_2017,
title = {Research activities on industrial wireless instrumentation: Brazilian perspective},
author = {Bertelli, G.; Santos, A.; Silva, I.; Fernandes, R.; Brandao, D.; Muller, I.; Netto, J.; Winter, J.; de Pereira, C.E.},
journal = {IEEE Instrumentation & Measurement Magazine},
year = {2017},
month = {4},
volume = {20},
number = {2},
institution = {Federal University of Rio Grande do Norte, Brazil; Federal University of Uberlandia, Brazil; University of Sao Paulo, Brazil; Federal University of Rio Grande do Sul, Brazil},
abstract = {Brazilian research activities in industrial wireless instrumentation have proven to be advanced and compelling, with papers being accepted in important journals, symposiums around the world, such as IFAC, ETFA, INDIN, I2MCT, ICIT, selected journals, and national conferences. This paper provides a glimpse of the research in industrial wireless instrumentation analysis over the past few years, and focuses on papers published by Brazilian researchers from the Federal University of Rio Grande do Norte, Federal University of Rio Grande do Sul and University of Sao Paulo. },
issn = {1094-6969},
keywords = {Logic gates, Wireless communication, Wireless sensor networks, Communication system security, Protocols, Instruments, Standards},
language = {English},
publisher = {IEEE},
pages = {21-30}
}

Brazilian research activities in industrial wireless instrumentation have proven to be advanced and compelling, with papers being accepted in important journals, symposiums around the world, such as IFAC, ETFA, INDIN, I2MCT, ICIT, selected journals, and national conferences. This paper provides a glimpse of the research in industrial wireless instrumentation analysis over the past few years, and focuses on papers published by Brazilian researchers from the Federal University of Rio Grande do Norte, Federal University of Rio Grande do Sul and University of Sao Paulo.

Wireless networked control systems (WNCS) are composed of spatially distributed sensors, actuators, and controllers communicating through wireless networks instead
of conventional point-to-point wired connections. Due to their main benefits in the reduction of deployment and maintenance costs, large flexibility and possible enhancement of safety, WNCS are becoming a fundamental infrastructure technology for critical control systems in automotive electrical systems, avionics control systems, building management systems, and industrial automation systems. The main challenge in WNCS is to jointly design the communication and control systems considering their tight interaction to improve the control performance and the network lifetime. In this survey, we make an exhaustive review of the literature on wireless network design and optimization for WNCS. First, we discuss what we call the critical interactive variables including sampling period, message delay, message dropout, and network energy consumption. The mutual effects of these communication and control variables motivate their joint tuning. We discuss the effect of controllable wireless network parameters at all layers of the communication protocols on the probability distribution of these interactive variables. We also review the current wireless network standardization for WNCS and their corresponding methodology for adapting the network parameters. Moreover, we discuss the analysis and design of control systems taking into account the effect of the interactive variables on the control system performance. Finally, we present the state-of-the-art wireless network design and optimization for WNCS, while highlighting the tradeoff between the achievable performance and complexity of various approaches. We conclude
the survey by highlighting major research issues and identifying future research directions.

@article{chevalier_2016,
title = {A Three-Year Feedback Study of a Remote Laboratory Used in Control Engineering Studies},
author = {Chevalier, A.; Copot, C.; Ionescu, C.; De Keyser, R.},
journal = {IEEE Transactions on Education},
year = {2016},
institution = {Department of Electrical Energy, Systems and Automation, Research Group Dynamical Systems and Control, Ghent University, Belgium},
abstract = {This paper discusses the results of a feedback study for a remote laboratory used in the education of control engineering students. The goal is to show the effectiveness of the remote laboratory on examination results. To provide an overview, the two applications of the remote laboratory are addressed: 1) the Stewart platform, and 2) the quadruple water tank system. Combining both applications allows a broad spectrum of practical examples featuring challenging control aspects such as multiple-input-multiple-output control, decoupling, non-minimum phase systems, open-loop unstable systems, and PID control design. The remote laboratory feedback study was performed using a five-point Likert-type scale survey to elicit the students' level of satisfaction with the laboratory. Three years of student examination results were also studied to compare performance before and after integrating the remote laboratory. In the first of these years there was no use of the remote laboratory. In the second year, the remote laboratory was introduced on a voluntary basis, and in the third year the remote laboratory was obligatory. Student feedback indicates that the remote laboratory needs further development to counter its limitations. A major conclusion of the survey was that there is keen interest in the remote laboratory to provide practical experience in the training of a control engineer. It can be concluded that the remote laboratory has a positive effect on student examination results. },
keywords = {Control engineering, feedback, higher education, remote laboratory, student experience},
language = {English},
publisher = {IEEE}
}

This paper discusses the results of a feedback study for a remote laboratory used in the education of control engineering students. The goal is to show the effectiveness of the remote laboratory on examination results. To provide an overview, the two applications of the remote laboratory are addressed: 1) the Stewart platform, and 2) the quadruple water tank system. Combining both applications allows a broad spectrum of practical examples featuring challenging control aspects such as multiple-input-multiple-output control, decoupling, non-minimum phase systems, open-loop unstable systems, and PID control design. The remote laboratory feedback study was performed using a five-point Likert-type scale survey to elicit the students' level of satisfaction with the laboratory. Three years of student examination results were also studied to compare performance before and after integrating the remote laboratory. In the first of these years there was no use of the remote laboratory. In the second year, the remote laboratory was introduced on a voluntary basis, and in the third year the remote laboratory was obligatory. Student feedback indicates that the remote laboratory needs further development to counter its limitations. A major conclusion of the survey was that there is keen interest in the remote laboratory to provide practical experience in the training of a control engineer. It can be concluded that the remote laboratory has a positive effect on student examination results.

@article{yaman_2016,
title = {Black Box Model and Evolutionary Fuzzy Control Methods of Coupled-Tank System},
author = {Yaman, S.; Rostami, S.},
journal = {International Journal of Electrical, Computer, Energetic, Electronic and Communication Engineering},
year = {2016},
volume = {10},
number = {6},
abstract = {In this study, a black box modeling of the coupledtank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability },
keywords = {Function tuner method, fuzzy modeling, fuzzy PID controller, genetic algorithm},
language = {English},
publisher = {WASET}
}

In this study, a black box modeling of the coupledtank system is obtained by using fuzzy sets. The derived model is tested via adaptive neuro fuzzy inference system (ANFIS). In order to achieve a better control performance, the parameters of three different controller types, classical proportional integral controller (PID), fuzzy PID and function tuner method, are tuned by one of the evolutionary computation method, genetic algorithm. All tuned controllers are applied to the fuzzy model of the coupled-tank experimental setup and analyzed under the different reference input values. According to the results, it is seen that function tuner method demonstrates better robust control performance and guarantees the closed loop stability

@article{coronado_2016,
title = {Cascaded Model-Free Fuzzy Control: an Application to the Coupled Tanks System},
author = {Coronado, A.; Aguiar, B.; Bernal, M.},
journal = {International Journal of Engineering Research & Science (IJOER)},
year = {2016},
volume = {2},
number = {4},
abstract = {This report proposes a design methodology for cascaded model-free fuzzy control systems. The ordinary Mamdani approach is modified in order to use expert knowledge for variable set-point control without any need of the system model. The methodology is successfully tested in a sub-actuated, naturally delayed setup, known as the coupled tanks system, where the water level is maintained at different set points, both in simulation and in real time. },
issn = {2395-6992},
keywords = {Cascade Systems, Coupled Tanks, Fuzzy Control, Variable Set Point Control},
language = {English},
pages = {143-150}
}

This report proposes a design methodology for cascaded model-free fuzzy control systems. The ordinary Mamdani approach is modified in order to use expert knowledge for variable set-point control without any need of the system model. The methodology is successfully tested in a sub-actuated, naturally delayed setup, known as the coupled tanks system, where the water level is maintained at different set points, both in simulation and in real time.

@article{basci_2016,
title = {Implementation of an adaptive fuzzy compensator for coupled tank liquid level control system},
author = {Basci, A.; Derdiyok, A.},
journal = {Measurement},
year = {2016},
volume = {91},
abstract = {In this paper, an adaptive fuzzy control (AFC) system is proposed to realize level position control of two coupled water tanks, often encountered in practical process control. The fuzzy control system includes an adaptive model identifier and controller. The gains of AFC are obtained by using the fuzzy identifier model which is defined by real system outputs and control inputs. The parameters of fuzzy identifier model are adjusted online by using recursive least square algorithm. Because the controller has a recursive form it treats model uncertainties and external disturbances in an implicit way. Thus there is no need to specify uncertainty and disturbances for this controller design in advance. A well-tuned conventional proportional integral (PI) controller is also applied to the two coupled tank system for comparison with the AFC system. Experimentation of the coupled tank system is realized in two different configurations, namely configuration #1 and configuration #2 respectively. In configuration #1, the water level in the top tank is controlled by a pump. In configuration #2, the water level in the bottom tank is controlled by the water flow coming out of the top tank. Experimental results prove that the AFC shows better trajectory tracking performance than PI controller in that the plant transient responses to the desired output changes have shorter settling time and smaller magnitude overshot/undershoot. Robustness of the AFC with respect to water level variation and capability to eliminate external disturbances are also achieved. Experimental results show that AFC is a strong and a practical choice for liquid level control. },
keywords = {Adaptive control; Fuzzy control; Nonlinear control; Process control},
language = {English},
publisher = {Elsevier Ltd.},
pages = {18-Dec}
}

In this paper, an adaptive fuzzy control (AFC) system is proposed to realize level position control of two coupled water tanks, often encountered in practical process control. The fuzzy control system includes an adaptive model identifier and controller. The gains of AFC are obtained by using the fuzzy identifier model which is defined by real system outputs and control inputs. The parameters of fuzzy identifier model are adjusted online by using recursive least square algorithm. Because the controller has a recursive form it treats model uncertainties and external disturbances in an implicit way. Thus there is no need to specify uncertainty and disturbances for this controller design in advance. A well-tuned conventional proportional integral (PI) controller is also applied to the two coupled tank system for comparison with the AFC system. Experimentation of the coupled tank system is realized in two different configurations, namely configuration #1 and configuration #2 respectively. In configuration #1, the water level in the top tank is controlled by a pump. In configuration #2, the water level in the bottom tank is controlled by the water flow coming out of the top tank. Experimental results prove that the AFC shows better trajectory tracking performance than PI controller in that the plant transient responses to the desired output changes have shorter settling time and smaller magnitude overshot/undershoot. Robustness of the AFC with respect to water level variation and capability to eliminate external disturbances are also achieved. Experimental results show that AFC is a strong and a practical choice for liquid level control.

@conference{maxim_2016,
title = {Modelling and identification of a coupled sextuple water tank system},
author = {Maxim, A.; Ionescu, C.; De keyser, R.},
booktitle = {2016 IEEE International Conference on Automation, Quality and Testing, Robotics (AQTR)},
year = {2016},
institution = {Ghent University, Department of Electrical energy, Systems and Automation, Belgium},
abstract = {This paper presents the modelling and identification procedure applied to a coupled, non-minimum phase system consisting of six water tanks. This process is composed of three inter-connected sub-systems coupled through the inputs. Using the process description, the theoretical nonlinear model was derived and linearised around a chosen operating point. After that, a three part experiment was conducted on the sextuple plant from Quanser in which one of the system's inputs was varied while the others remained constant. The experimental data was used to compute the system's static characteristic which describes the output variation limits for different input values. Then, the dynamic characteristic was used to analyse the system evolution in transient time to provide insight knowledge about the model orders required in the parametric identification. The results obtained clearly show that the computed linear model proper characterizes the dynamics of the real process and can be further used in simulations. },
keywords = {nonlinear model, parametric identification, static characteristic, dynamic characteristic, sextuple tank process},
language = {English},
publisher = {IEEE},
isbn = {978-1-4673-8691-3}
}

This paper presents the modelling and identification procedure applied to a coupled, non-minimum phase system consisting of six water tanks. This process is composed of three inter-connected sub-systems coupled through the inputs. Using the process description, the theoretical nonlinear model was derived and linearised around a chosen operating point. After that, a three part experiment was conducted on the sextuple plant from Quanser in which one of the system's inputs was varied while the others remained constant. The experimental data was used to compute the system's static characteristic which describes the output variation limits for different input values. Then, the dynamic characteristic was used to analyse the system evolution in transient time to provide insight knowledge about the model orders required in the parametric identification. The results obtained clearly show that the computed linear model proper characterizes the dynamics of the real process and can be further used in simulations.

@conference{bertelli_2016,
title = {Performance Evaluation of ISA100.11a Wireless Feedback Control},
author = {Bertelli, G.; Santos, A.; Cesar, J.; Silva, I.},
booktitle = {4th IFAC Symposium on Telematics Applications (TA 2016)},
year = {2016},
institution = {Federal University of Rio Grande do Norte, Brazil},
abstract = {Nowadays, wireless communication is a tendency in industrial environments, saving resources and enabling the addition of new applications when compared to their wired counterparts. In this context, the ISA100.11a specification is emerging as a solution for the last mile connection. Despite its high degree of applicability, due to the nature of its technical challenges (reliability, energy consumption, fault tolerance, ensuring constant delays) an ISA100.11a network is used, in the majority of applications, for monitoring processes. Given the aforementioned and considering the lack of commercial wireless actuators, the demand for evaluation and assured reliability tools on the control loops is imminent. Aiming to demystify the use of wireless technology on the control loops in the industry, this paper presents a practical experiment of evaluation that enables the analysis of the behavior of an ISA100.11a network in process control by controlling the level of water in a system of coupled tanks, part of a Quanser's educational kit. },
keywords = {Wireless control; ISA100.11a; industrial wireless networks},
language = {English},
publisher = {Elsevier Ltd.}
}

Nowadays, wireless communication is a tendency in industrial environments, saving resources and enabling the addition of new applications when compared to their wired counterparts. In this context, the ISA100.11a specification is emerging as a solution for the last mile connection. Despite its high degree of applicability, due to the nature of its technical challenges (reliability, energy consumption, fault tolerance, ensuring constant delays) an ISA100.11a network is used, in the majority of applications, for monitoring processes. Given the aforementioned and considering the lack of commercial wireless actuators, the demand for evaluation and assured reliability tools on the control loops is imminent. Aiming to demystify the use of wireless technology on the control loops in the industry, this paper presents a practical experiment of evaluation that enables the analysis of the behavior of an ISA100.11a network in process control by controlling the level of water in a system of coupled tanks, part of a Quanser's educational kit.

@conference{maxim_2016,
title = {Reference Tracking using a Non-Cooperative Distributed Model Predictive Control Algorithm},
author = {Maxim, A.; Ionescu, C.M.; Caruntu, C.F.; Lazar, C.; De Keyser, R.},
booktitle = {11th IFAC Symposium on Dynamics and Control of Process Systems},
year = {2016},
abstract = {In this paper, a non-cooperative distributed model predictive control (DMPC) algorithm for tracking constant references is developed and evaluated. As such, an augmented model is employed (i.e. the control loop is embedded with integrators) and the augmented state contains the state increments and the error between the reference and the predicted output. The algorithm is tested in real life experiments on the quadruple tank process with non-minimum phase behaviour. The experimental results show acceptable performance index for the DMPC method when compared with the centralized approach. },
keywords = {non-cooperative DMPC, reference tracking, two agent systems, MIMO systems, non-minimum phase systems},
publisher = {IFAC},
pages = {1079-1084}
}

In this paper, a non-cooperative distributed model predictive control (DMPC) algorithm for tracking constant references is developed and evaluated. As such, an augmented model is employed (i.e. the control loop is embedded with integrators) and the augmented state contains the state increments and the error between the reference and the predicted output. The algorithm is tested in real life experiments on the quadruple tank process with non-minimum phase behaviour. The experimental results show acceptable performance index for the DMPC method when compared with the centralized approach.

@conference{granado_2016,
title = {Remote experimentation using a smartphone application with haptic feedback},
author = {Granado, E.; Quizhpi, F.; Colmenares, W.},
booktitle = {2016 IEEE Global Engineering Education Conference (EDUCON)},
year = {2016},
abstract = {This paper presents the development of a remote experimentation for automatic control engineering education. By using a smartphone application, students can interact with real laboratory didactic equipment. Through a friendly graphical user interface and information provided by built-in smartphone sensors, students can modify the process parameters and verify in real time what's happening on the experimental setup. Mobile device vibration technology is used to add haptic tactile feedback to the application. This additional sense complements the visual and hearing information the user usually acquires when performing a practical experience. Therefore, students pay more attention to the results achieved online. Taking advantage of today's smartphone technological features, the students feel highly motivated to use this device to achieve improvements in their learning process. To reach a great number of users, the application runs across the most widely used mobile platforms. All user lab activities are stored in a database for the teacher later analysis. Likewise, students can store the resulted experiments on their mobile device when finished in order to make an off-line result analysis. },
keywords = {adobe AIR; control engineering education; haptic feedback; remote experimentation; technology enhanced learning},
language = {English},
publisher = {IEEE},
pages = {240-247}
}

This paper presents the development of a remote experimentation for automatic control engineering education. By using a smartphone application, students can interact with real laboratory didactic equipment. Through a friendly graphical user interface and information provided by built-in smartphone sensors, students can modify the process parameters and verify in real time what's happening on the experimental setup. Mobile device vibration technology is used to add haptic tactile feedback to the application. This additional sense complements the visual and hearing information the user usually acquires when performing a practical experience. Therefore, students pay more attention to the results achieved online. Taking advantage of today's smartphone technological features, the students feel highly motivated to use this device to achieve improvements in their learning process. To reach a great number of users, the application runs across the most widely used mobile platforms. All user lab activities are stored in a database for the teacher later analysis. Likewise, students can store the resulted experiments on their mobile device when finished in order to make an off-line result analysis.

@conference{ionescu_2016,
title = {Robust PID Auto-tuning for the Quadruple Tank System},
author = {Ionescu, C.M.; Maxim, A.; Copot, C.; De Keyser, R.},
booktitle = {11th IFAC Symposium on Dynamics and Control of Process Systems},
year = {2016},
abstract = {In multi-modular process architectures with independent but interacting subsystems, identi cation may not be the rst choice at hand for closed loop control. A robust relay-based PID autotuning strategy is presented and validated on a quadruple tank system with non-minimum phase dynamics. The controller ensures a speci ed closed loop robustness, which is of great bene t to the overall performance. The experimental results suggest that the proposed method ful ls the robustness requirement and performs well in various operating conditions of the testbench. },
keywords = {Robustness, Non-minimum phase systems, Multivariable control systems},
language = {English},
publisher = {IFAC},
pages = {919-924}
}

In multi-modular process architectures with independent but interacting subsystems, identi cation may not be the rst choice at hand for closed loop control. A robust relay-based PID autotuning strategy is presented and validated on a quadruple tank system with non-minimum phase dynamics. The controller ensures a speci ed closed loop robustness, which is of great bene t to the overall performance. The experimental results suggest that the proposed method ful ls the robustness requirement and performs well in various operating conditions of the testbench.

@conference{chevalier_2015,
title = {Development and student evaluation of an Internet-based Control Engineering Laboratory},
author = {Chevalier, A.; Bura, M.; Copot, C.; Ionescu, C.; De Keyser, R.},
booktitle = {3rd IFAC Workshop on Internet Based Control Education},
year = {2015},
institution = {Ghent University, Belgium},
abstract = {This paper presents the structure, functionality and application of an improved Re- mote Laboratory for engineering students hosted at Ghent University. The Remote Laboratory consists of two setups: Ball and Plate system and Quadruple Water Tank system. These setups introduce basic control aspects such as PID control design and non-minimum phase systems. Also more challenging aspects such as multiple-input-multiple-output control, decoupled and decentralized systems and advanced control strategies such as Internal Model Control or Model Predictive Control can be investigated on the setups. Based on a feedback study that targeted the bachelor degree students, the level of e ectiveness of this concept has been shown but also possible functional enhancements that can be applied to the systems have been pointed out. The feedback survey data concluded that the Remote Laboratory has attracted the attention of students and had a positive impact in their training. },
keywords = {Remote Laboratory, Control engineering, Feedback study, Ball and Plate, Quadruple Water Tank},
language = {English},
publisher = {IFAC}
}

This paper presents the structure, functionality and application of an improved Re- mote Laboratory for engineering students hosted at Ghent University. The Remote Laboratory consists of two setups: Ball and Plate system and Quadruple Water Tank system. These setups introduce basic control aspects such as PID control design and non-minimum phase systems. Also more challenging aspects such as multiple-input-multiple-output control, decoupled and decentralized systems and advanced control strategies such as Internal Model Control or Model Predictive Control can be investigated on the setups. Based on a feedback study that targeted the bachelor degree students, the level of e ectiveness of this concept has been shown but also possible functional enhancements that can be applied to the systems have been pointed out. The feedback survey data concluded that the Remote Laboratory has attracted the attention of students and had a positive impact in their training.

@article{de-castro_2015,
title = {Exponential Mapping Function for Nonlinear Control},
author = {de Castro, H.; Paglione, P.; Ribeiro, C.},
journal = {Studies in Informatics and Control}},
year = {2015},
volume = {24},
number = {4},
institution = {Aeronautics Technological Institute, Brazil},
abstract = {Industrial control engineers, who are often faced with the problem of dealing with projects involving unknown or poorly modelled systems, usually have at their disposal a limited number of options to develop, implement, and maintain controllers, namely PID and, lately, fuzzy-based controllers. The large use of the PID controller comes from the widespread knowledge of its theory and easy tuning methods and its prompt availability in control equipment and supervisory systems. Nevertheless, depending on the manufacturer’s discretion, at least five gains have to be set. Fuzzy controllers for a SISO system usually demand between fifteen and twenty parameters. That’s also a problem for the maintenance personnel. The proposed SISO controller needs two heuristically defined gains to be set, based on knowledge about the free response of the plant and expected disturbances. Its simplicity allows its implementation on devices with memory and processor constraints. },
keywords = {Nonlinear control, Sliding-Mode Control, Fuzzy Logic Control},
language = {English},
pages = {449-460}
}

Industrial control engineers, who are often faced with the problem of dealing with projects involving unknown or poorly modelled systems, usually have at their disposal a limited number of options to develop, implement, and maintain controllers, namely PID and, lately, fuzzy-based controllers. The large use of the PID controller comes from the widespread knowledge of its theory and easy tuning methods and its prompt availability in control equipment and supervisory systems. Nevertheless, depending on the manufacturer’s discretion, at least five gains have to be set. Fuzzy controllers for a SISO system usually demand between fifteen and twenty parameters. That’s also a problem for the maintenance personnel. The proposed SISO controller needs two heuristically defined gains to be set, based on knowledge about the free response of the plant and expected disturbances. Its simplicity allows its implementation on devices with memory and processor constraints.

@article{tang_2015,
title = {Identification of nonlinear discrete systems by a state-space recurrent neurofuzzy network with a convergent algorithm},
author = {Gonzalez-Olvera, M.A. ; Tang, Y.},
journal = {Neurocomputing},
year = {2015},
volume = {148},
abstract = {Recurrent neurofuzzy networks have proven to be useful in identification of systems with unknown dynamics when only input_output information is available. However, training algorithms for these structures usually require also the measurement of the actual states of the system in order to obtain a convergent algorithm and then obtain a scheme to approximate its dynamic behavior. When states are not available and only input_output information can be obtained, the stability of the training algorithm of the recurrent networks is hard to establish, as the dynamics is driven by the internal recurrent dynamics of each connection. In this paper, we present a structure and an ultimately stable training algorithm inspired by adaptive observer for black-box identification based on state-space recurrent neural networks for a class of dynamic nonlinear systems in discrete-time. The network catches the dynamics of the unknown plant and jointly identifies its parameters using only output measurements, with ultimately bounded identification and parameter error. Numerical examples using simulated and experimental systems are included to illustrate the effectiveness of the proposed method. },
keywords = {Neural-network models; Fuzzy modeling; System identification; Discrete-time systems},
language = {English},
publisher = {Elsevier B.V.},
pages = {318-325}
}

Recurrent neurofuzzy networks have proven to be useful in identification of systems with unknown dynamics when only input_output information is available. However, training algorithms for these structures usually require also the measurement of the actual states of the system in order to obtain a convergent algorithm and then obtain a scheme to approximate its dynamic behavior. When states are not available and only input_output information can be obtained, the stability of the training algorithm of the recurrent networks is hard to establish, as the dynamics is driven by the internal recurrent dynamics of each connection. In this paper, we present a structure and an ultimately stable training algorithm inspired by adaptive observer for black-box identification based on state-space recurrent neural networks for a class of dynamic nonlinear systems in discrete-time. The network catches the dynamics of the unknown plant and jointly identifies its parameters using only output measurements, with ultimately bounded identification and parameter error. Numerical examples using simulated and experimental systems are included to illustrate the effectiveness of the proposed method.

@conference{araujo_2015,
title = {Nonlinear System Identification based on Modified ANFIS},
author = {da Cost Martins, J.K.E.; de Araujo, F.M.U.},
booktitle = {12th International Conference on Informatics in Control, Automation and Robotics},
year = {2015},
institution = {Universidade Federal do Rio Grande do Norte, Brazil},
abstract = {This article aims to present the nonlinear system identification by the method of modified ANFIS. The modified ANFIS is a structure proposed that is based on the traditional structure of ANFIS with some modifications as shown in the article. The importance of the choice of method parameters and its influence on the system will be discussed. For this, the identification of a coupled system of tanks with nonlinear dynamics is performed. System identification will be performed by changing the inputs and order of the consequent model and then will perform a review of the systems. The results confirm the simplicity of modified ANFIS in comparison with the traditional ANFIS while have good performance in the identification of nonlinear systems. },
keywords = {ANFIS, Modified ANFIS, Nonlinear Systems Identification, Linear Systems Identification},
language = {English},
pages = {588-595}
}

This article aims to present the nonlinear system identification by the method of modified ANFIS. The modified ANFIS is a structure proposed that is based on the traditional structure of ANFIS with some modifications as shown in the article. The importance of the choice of method parameters and its influence on the system will be discussed. For this, the identification of a coupled system of tanks with nonlinear dynamics is performed. System identification will be performed by changing the inputs and order of the consequent model and then will perform a review of the systems. The results confirm the simplicity of modified ANFIS in comparison with the traditional ANFIS while have good performance in the identification of nonlinear systems.

@article{khadraoui_2014,
title = {A measurement-based technique for designing fixed-order RST controllers and application to a coupled water tank system},
author = {Sofiane Khadraoui, Hazem N. Nounou, Mohamed N. Nounou, Aniruddha Datta and Shankar P. Bhattacharyya},
journal = {Systems Science & Control Engineering},
year = {2014},
volume = {2},
number = {1},
abstract = {This paper addresses the control design problem for unknown linear single-input single-output systems using a set of measurements. In standard control methods, controllers are designed on the basis of a mathematical model. Such a mathematical model, which describes the behavior of the system, can be developed using either physical laws or measured data. However, due to the complex dynamics of many physical systems, some prior assumptions are usually made to build simplified models. The efficacy of such model-based control techniques depends greatly on the quality of models used. Hence, data-based control design methods appeared as an alternative to model-based methods. Such data-based techniques are powerful in the sense that no mathematical model is needed for controller design. In this paper, we propose an approach that uses frequency response data to directly design controllers without going through any modeling stage. The main idea of our proposed method is to design polynomial RST controllers, for which the closed-loop frequency response fits a desired frequency response that describes some desired performance specifications. This problem is formulated as an error minimization problem, which can be solved using efficient optimization algorithms. The main feature of our proposed control approach is that it enables the designer to pre-select the controller structure, which allows the design of low-order controllers. Moreover, this control design approach does not depend on the increasing order and complexity of the system. An application to water level control of a coupled tank system is presented to validate and illustrate the efficacy of the proposed approach. },
keywords = {measurement-based control; polynomial RST controller; low-order controller; unknown dynamical systems; error minimization},
language = {English},
publisher = {Taylor & Francis},
pages = {484-492}
}

This paper addresses the control design problem for unknown linear single-input single-output systems using a set of measurements. In standard control methods, controllers are designed on the basis of a mathematical model. Such a mathematical model, which describes the behavior of the system, can be developed using either physical laws or measured data. However, due to the complex dynamics of many physical systems, some prior assumptions are usually made to build simplified models. The efficacy of such model-based control techniques depends greatly on the quality of models used. Hence, data-based control design methods appeared as an alternative to model-based methods. Such data-based techniques are powerful in the sense that no mathematical model is needed for controller design. In this paper, we propose an approach that uses frequency response data to directly design controllers without going through any modeling stage. The main idea of our proposed method is to design polynomial RST controllers, for which the closed-loop frequency response fits a desired frequency response that describes some desired performance specifications. This problem is formulated as an error minimization problem, which can be solved using efficient optimization algorithms. The main feature of our proposed control approach is that it enables the designer to pre-select the controller structure, which allows the design of low-order controllers. Moreover, this control design approach does not depend on the increasing order and complexity of the system. An application to water level control of a coupled tank system is presented to validate and illustrate the efficacy of the proposed approach.

@article{valand_2014,
title = {An analysis of self tuning Fuzzy PID – IMC for coupled water two tank system},
author = {Valand, P.A.; Patel, A.; Solanki, H.},
journal = {International Journal of Engineering Development and Research},
year = {2014},
abstract = {Nowadays the simplest and effective solutions to most of the control engineering applications are provided by PID controllers. However PID controllers are poorly tuned in practice with most of the tuning is done manually which is difficult and time consuming. This article comes up with new approaches of Fuzzy-IMC to design of PID controller for coupled water tank system at tank-1. The coupled water two tank system has limitations and it is difficult to control optimally using only PID controllers as the parameters of the system are changing constantly. The liquid level of two coupled water tank system is taken as an object. MATLAB software is used to design Fuzzy-IMC control at tank-1 then analyze the control effect. As a result, it is found that Fuzzy-IMC gives faster rise time, no overshoot, good steady quality with shorter adjusting time and smaller steady state error. },
issn = {2321-9939},
keywords = {fuzzy self tuning, PID-IMC, Mathematical model of coupled tank system, Evaluationary Algorithm},
language = {English}
}

Nowadays the simplest and effective solutions to most of the control engineering applications are provided by PID controllers. However PID controllers are poorly tuned in practice with most of the tuning is done manually which is difficult and time consuming. This article comes up with new approaches of Fuzzy-IMC to design of PID controller for coupled water tank system at tank-1. The coupled water two tank system has limitations and it is difficult to control optimally using only PID controllers as the parameters of the system are changing constantly. The liquid level of two coupled water tank system is taken as an object. MATLAB software is used to design Fuzzy-IMC control at tank-1 then analyze the control effect. As a result, it is found that Fuzzy-IMC gives faster rise time, no overshoot, good steady quality with shorter adjusting time and smaller steady state error.

@article{veronesi_2014,
title = {Automatic Tuning of Feedforward Controllers for Disturbance Rejection},
author = {Veronesi, M.; Visioli, A.},
journal = {Ind. Eng. Chem. Res},
year = {2014},
volume = {53},
number = {7},
abstract = {We propose a method for the automatic tuning of the feedforward compensator for proportional-integral-derivative control loops in order to reject disturbances acting on the process. The parameters of the compensator are automatically computed after estimating the disturbance transfer function by using closed-loop routine operating data. Simulation and experimental results show the effectiveness of the methodology. },
language = {English},
publisher = {American Chemical Society},
pages = {2764_2770}
}

We propose a method for the automatic tuning of the feedforward compensator for proportional-integral-derivative control loops in order to reject disturbances acting on the process. The parameters of the compensator are automatically computed after estimating the disturbance transfer function by using closed-loop routine operating data. Simulation and experimental results show the effectiveness of the methodology.

@inproceedings{santos_2014,
title = {Avaliacao de redes wirelesshart em malhas de controle},
author = {Santos, A.; Lopes, D.; Silva I.; Cesar, J.; Luciano L.; Neto, A.; Guedes, L.A.},
booktitle = {Anais do XX Congresso Brasileiro de Automàtica},
year = {2014},
abstract = {Nowadays wireless communication is a tendency in industry environments, saving resources and enabling the addition of new applications when compared to their wired counterparts. In this context, the WirelessHART speci cation is emerging as a solution for the last mile connection. Despite its high degree of applicability, a WirelessHART network faces some technical (reliability, energy consumption, fault tolerance, ensuring constant delays) and cultural challenges. Thus, the demanding for evaluation and ensure reliability tools on the control loops is imminent. Aiming to demystify the use of wireless technology on the control loops in the industry, this paper presents an evaluation that enables to analyze the behavior of a WirelessHART network in a process of controlling the level of water in a system of coupled tanks, part of a Quanser's educational kit. },
keywords = {WirelessHART, control, industrial wireless networks, XML-RPC},
language = {Portuguese},
pages = {2593-2600}
}

Nowadays wireless communication is a tendency in industry environments, saving resources and enabling the addition of new applications when compared to their wired counterparts. In this context, the WirelessHART speci cation is emerging as a solution for the last mile connection. Despite its high degree of applicability, a WirelessHART network faces some technical (reliability, energy consumption, fault tolerance, ensuring constant delays) and cultural challenges. Thus, the demanding for evaluation and ensure reliability tools on the control loops is imminent. Aiming to demystify the use of wireless technology on the control loops in the industry, this paper presents an evaluation that enables to analyze the behavior of a WirelessHART network in a process of controlling the level of water in a system of coupled tanks, part of a Quanser's educational kit.

@inproceedings{kleiton_2014,
title = {Desenvolvimento de um Ambiente Computacional para Ensino de Controle Fuzzy},
author = {Jose Kleiton Ewerton da Costa Martins, Mario Sergio Freitas Ferreira Cavalcante, Fabio Ricardo de Lima Souza, Fabio Meneghetti Ugulino de Araujo},
booktitle = {Anais do XX Congresso Brasileiro de Automàtica 2014},
year = {2014},
institution = {Universidade Federal do Rio Grande do Norte, Brazil},
abstract = {This paper presents the design and implementation of a software that was developed for help any student to learn Fuzzy logic control, it provides a simple, functional and very intuitive user interface and also has a freeware license. This software was developed in C++ with the assist of Sockets to communicate the plant with the appplication. Knows that, the simulations are frequent when studying Fuzzy logic controller, the software already contains an environment in which use a didactic kit to the student demonstrate the effciency of your controller. },
keywords = {Fuzzy Control, Engineering Education, Educational Software, Educational Kit},
language = {Portuguese},
pages = {1434-1441}
}

This paper presents the design and implementation of a software that was developed for help any student to learn Fuzzy logic control, it provides a simple, functional and very intuitive user interface and also has a freeware license. This software was developed in C++ with the assist of Sockets to communicate the plant with the appplication. Knows that, the simulations are frequent when studying Fuzzy logic controller, the software already contains an environment in which use a didactic kit to the student demonstrate the effciency of your controller.

@article{subha_2014,
title = {Implementation of predictive controllers for NMAS consensus with neighhour agent delay},
author = {Subha, N.A.m.; Liu, G.},
booktitle = {2014 UKACC International Conference on Control},
year = {2014},
abstract = {This paper discusses the implementation of a prediction algorithm in solving an external consensus problem for heterogeneous networked multi-agent systems (NMAS) with asymmetric network-induced communication delay. By considering different networked-induced delays for each information passing route between agents, an output predictor based on the recursive equation is developed. The developed strategy is simulated with a single-input single-output (SISO) NMAS model and validated through practical experiments with water level test rigs under intranet network connections. },
keywords = {predictive control, networked multi-agent, recursive, SISO, communication delay},
language = {English},
publisher = {IEEE},
pages = {238 - 243}
}

This paper discusses the implementation of a prediction algorithm in solving an external consensus problem for heterogeneous networked multi-agent systems (NMAS) with asymmetric network-induced communication delay. By considering different networked-induced delays for each information passing route between agents, an output predictor based on the recursive equation is developed. The developed strategy is simulated with a single-input single-output (SISO) NMAS model and validated through practical experiments with water level test rigs under intranet network connections.

@article{patel_2014,
title = {Tuning of Classical Controller Using Evolutionary Method for Real Time System},
author = {Patel, R.B.},
journal = {International Journal of Engineering Trends and Technology (IJETT)},
year = {2014},
volume = {12},
number = {5},
institution = {Sardar Vallabhbhai Patel Institute of Technology, India},
abstract = {The objective of this paper is to design and comparative analysis of classical controller tuning using traditional and evolutionary methods for real time system. To achieve this objective, the nonlinear water tank control has been selected as real time system. The proposal- integral-derivative control law is used as control algorithm in controller. The tuning parameters as propositional gain, integral gain and derivative gain are tuned using traditional method and evolutionary method. The performance of both methods are compared and discussed with considering hard constraint of real time system. },
issn = {2231-5381},
keywords = {Classical controller, Genetic algorithm, Matlab, Quarc Software, Real time system, PID tuning},
language = {English},
pages = {255-257}
}

The objective of this paper is to design and comparative analysis of classical controller tuning using traditional and evolutionary methods for real time system. To achieve this objective, the nonlinear water tank control has been selected as real time system. The proposal- integral-derivative control law is used as control algorithm in controller. The tuning parameters as propositional gain, integral gain and derivative gain are tuned using traditional method and evolutionary method. The performance of both methods are compared and discussed with considering hard constraint of real time system.

@article{beschi_2014,
title = {Two degree-of-freedom design for a send-on-delta sampling PI control strategy},
author = {Beschi, M.; Dormido, S.; Sanchez, J.; Visioli, A.},
journal = {Control Engineering Practice},
year = {2014},
volume = {30},
abstract = {A complete event-based two-degree-of-freedom PI controller is presented. The architecture of the control system is based on two decoupled PI controllers, one for the set-point following and one for the load disturbance rejection task. The distinctive feature of the proposed approach is that the two controllers have the same parameters and the reference tracking performance is improved by suitably modifying the reference signal applied to the set-point following controller. Examples of the technique are given. In particular, the control strategy has been applied to a distributed solar collector field. },
keywords = {Event-based PI control, Two-degree-of-freedom strategy, Tuning, Feedforward control, Solar collector field},
language = {English},
publisher = {Elsevier Ltd.},
pages = {55-66}
}

A complete event-based two-degree-of-freedom PI controller is presented. The architecture of the control system is based on two decoupled PI controllers, one for the set-point following and one for the load disturbance rejection task. The distinctive feature of the proposed approach is that the two controllers have the same parameters and the reference tracking performance is improved by suitably modifying the reference signal applied to the set-point following controller. Examples of the technique are given. In particular, the control strategy has been applied to a distributed solar collector field.

@article{musmade_2013,
title = {Feedforward-plus-sliding mode controller design with experimental application of coupled tank system},
author = {Musmade, B.B.; Patre, B.M.},
journal = {Transactions of the Institute of Measurements and Control},
year = {2013},
volume = {35},
number = {8},
institution = {SGGS Institute of Engineering and Technology, Nanded, India},
abstract = {In this paper, a feedforward-plus-sliding mode controller is proposed. The combination uses a feedforward controller to achieve predefined proces s output and the sliding mode controller is combined to assure the robustness despite uncertainty, nonlinear dynamics, and external disturbances. Th e effectiveness of proposed method is shown by simulations on nonlinear models of a coupled tanks system and then validated by performing a real-time experiment on the system. The studies show the improved setpoint tracking of the proposed controller compared with the classical PI controller. },
keywords = {Feedforward-plus-sliding mode controller, coupled tanks system, nonlinear dynamics},
language = {English},
publisher = {SAGE},
pages = {1058-1067}
}

In this paper, a feedforward-plus-sliding mode controller is proposed. The combination uses a feedforward controller to achieve predefined proces s output and the sliding mode controller is combined to assure the robustness despite uncertainty, nonlinear dynamics, and external disturbances. Th e effectiveness of proposed method is shown by simulations on nonlinear models of a coupled tanks system and then validated by performing a real-time experiment on the system. The studies show the improved setpoint tracking of the proposed controller compared with the classical PI controller.

@conference{pires_2013,
title = {Fuzzy Control Optimization Using Genetic Algorithm},
author = {Pires, A.H.M.; de Fig.U.ueiredo, A.R., Severino, A.G.V; da Silva, M.J.; de Araujo, F.M.},
booktitle = {11th Brazilian Symposium on Intelligent Automation (SBAI)},
year = {2013},
institution = {Universidade Federal do Rio Grande do Norte, Brazil},
abstract = {This paper talks about the optimization of a fuzzy controller by a genetic algorithm. The fuzzy systems are an alterna-tive to some problems, and in this work it is used to control a tank level. The fuzzy control that was used implements a simple strategy of the Proportional Derivative control and it is the Takagi-Sugeno-Kang type. The plant used is from the Tanks Quanser, and consists in two tanks and a pump, this plant were modeled and simulated in computer to test the fuzzy control optimized. To optimize the fuzzy control were used a genetic algorithm implemented in computer too and the results were compared with a hand tuned fuzzy control, analyzing by evaluation indices and graphics answer. },
keywords = {Genetic Algorithm, Optimization, Fuzzy, Control, Automation},
language = {Portuguese}
}

This paper talks about the optimization of a fuzzy controller by a genetic algorithm. The fuzzy systems are an alterna-tive to some problems, and in this work it is used to control a tank level. The fuzzy control that was used implements a simple strategy of the Proportional Derivative control and it is the Takagi-Sugeno-Kang type. The plant used is from the Tanks Quanser, and consists in two tanks and a pump, this plant were modeled and simulated in computer to test the fuzzy control optimized. To optimize the fuzzy control were used a genetic algorithm implemented in computer too and the results were compared with a hand tuned fuzzy control, analyzing by evaluation indices and graphics answer.

@conference{maxim_2013,
title = {Multivariable Model-Based Control Strategies for Level Control in a Quadruple Tank Process},
author = {Maxim, A.; Ionescu, C.M.; Copot, C.; De Keyser, R.; Lazar, C.},
booktitle = {2013 17th International Conference System Theory, Control and Computing (ICSTCC)},
year = {2013},
abstract = {This paper presents three model-based control strategies applied to a multivariable process. First, a simple and rather naive approach is employed, i.e. treating the process as two SISO (Single Input Single Output) loops and design PID controllers. Obviously, this approach is effective, but does not take into account the interaction between the loops. Next, interaction is compensated by using dynamic decouplers and control performance is improved. Finally, a multivariable IMC (Internal Model Control) method is applied. All the results were validated on the laboratory setup with coupled quadruple tanks from Quanser. This is an interesting and challenging testbed for control, i.e. it poses non-minimum phase transmission zeros. Our experimental results show that the IMC outperforms the PID control at the cost of additional design complexity. All controllers were successfully tested for setpoint trajectory and disturbance rejection and tackled well the noise in the system. },
keywords = {multivariable control, transmission zeros, nonminimum phase, decentralized control, decoupling control, internal model control},
publisher = {IEEE},
isbn = {978-1-4799-2227-7},
pages = {343-348}
}

This paper presents three model-based control strategies applied to a multivariable process. First, a simple and rather naive approach is employed, i.e. treating the process as two SISO (Single Input Single Output) loops and design PID controllers. Obviously, this approach is effective, but does not take into account the interaction between the loops. Next, interaction is compensated by using dynamic decouplers and control performance is improved. Finally, a multivariable IMC (Internal Model Control) method is applied. All the results were validated on the laboratory setup with coupled quadruple tanks from Quanser. This is an interesting and challenging testbed for control, i.e. it poses non-minimum phase transmission zeros. Our experimental results show that the IMC outperforms the PID control at the cost of additional design complexity. All controllers were successfully tested for setpoint trajectory and disturbance rejection and tackled well the noise in the system.

@article{derdiyok_2013,
title = {The application of chattering-free sliding mode controller in coupled tank liquid-level control system},
author = {Adnan Derdiyok, Abdullah Basci},
journal = {Korean Journal of Chemical Engineering},
year = {2013},
volume = {30},
number = {3},
institution = {Department of Electrical & Electronics Eng., Ataturk University, Turkey},
abstract = {A chattering-free sliding mode controller (CFSMC) is proposed to realize level position control of liquid level system for two coupled water tanks, as is often encountered in practical process control. The controller is used due to its robustness against large parameter variation, disturbances rejection and reduction in chattering. Experimentation of the coupled tank system is realized in two different configurations: configuration 1 and configuration 2. In configuration 1, the water level in the top tank is controlled by a pump. In 2, the water level in the bottom tank is controlled by the water flow coming out of the top tank. The validity of the proposed controller is verified by means of a practical testing on an experimental liquid level control device. },
issn = {0256-1115},
keywords = {Liquid Level Control System, Sliding Mode Control},
language = {English},
publisher = {Springer US},
pages = {540-545}
}

A chattering-free sliding mode controller (CFSMC) is proposed to realize level position control of liquid level system for two coupled water tanks, as is often encountered in practical process control. The controller is used due to its robustness against large parameter variation, disturbances rejection and reduction in chattering. Experimentation of the coupled tank system is realized in two different configurations: configuration 1 and configuration 2. In configuration 1, the water level in the top tank is controlled by a pump. In 2, the water level in the bottom tank is controlled by the water flow coming out of the top tank. The validity of the proposed controller is verified by means of a practical testing on an experimental liquid level control device.

@conference{keyser_2013,
title = {Validation of a multivariable Relay-Based PID Autotuner with Specified Robustness},
author = {De Keyser, R.; Maxim, A.; Copot, C.; Ionescu, C.M.},
booktitle = {2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA)},
year = {2013},
institution = {Ghent University Department of Electrical energy, Systems and Automation},
abstract = {This paper presents a multivariable relay-based PID autotuning strategy, which ensures a specified modulus margin (i.e. robustness). The algorithm is applied on the coupled quadruple tanks from Quanser. The system is challenging for control since it presents non-minimum phase transmission zeros. The performance of the autotuner is validated against a computer-aided design tool based on the frequency response, i.e. FRTool. The experimental results suggest that the proposed autotuning procedure has similar performance as the control design based on full knowledge of the system. This is a remarkable conclusion and provides a good motivation to claim that our algorithm may be useful in chemical process applications where full knowledge of the systems model is still a burden for the control engineer. },
keywords = {FRTool, Quanser, chemical process applications, computer-aided design tool, control design, coupled quadruple tanks, frequency response, modulus margin, multivariable relay-based PID autotuner, nonminimum phase transmission zeros, robustness},
publisher = {IEEE},
pages = {06-Jan}
}

This paper presents a multivariable relay-based PID autotuning strategy, which ensures a specified modulus margin (i.e. robustness). The algorithm is applied on the coupled quadruple tanks from Quanser. The system is challenging for control since it presents non-minimum phase transmission zeros. The performance of the autotuner is validated against a computer-aided design tool based on the frequency response, i.e. FRTool. The experimental results suggest that the proposed autotuning procedure has similar performance as the control design based on full knowledge of the system. This is a remarkable conclusion and provides a good motivation to claim that our algorithm may be useful in chemical process applications where full knowledge of the systems model is still a burden for the control engineer.

@conference{araujo_2012,
title = {Implementation of a J2ME Fuzzy Controller Embedded in a SUN SPOT Mobile Device},
author = {Ugulino de Araújo, M.E.; de Paiva Onofre Filho, M.; de Aguiar Correia Feliciano, R.; Ugulino de Araújo, F.M.; Costa Barros, D.M.},
booktitle = {ABCM Symposium Series in Mechatronics },
year = {2012},
volume = {5},
institution = {Federal Institute of Education, Science and Technology of Paraíba, Brazil; Federal University of Rio Grande do Norte, Brazil},
abstract = { Fuzzy intelligent systems are present in a variety of equipment, ranging from household appliances to small devices like digital cameras and cell phones, being used primarily for dealing with the uncertainties in the modeling of real systems, which are typically nonlinear. However, commercial implementations of fuzzy systems are not general purpose and do not have portability to different hardware platforms. Thinking about it, this paper proposes the implementation of a system capable of generating a Takagi-Sugeno fuzzy controller written in Java To Platform Micro Edition (J2ME), whose modular design makes it portable to any mobile device that supports J2ME. Thus, the proposed development platform is capable of generating all classes of a controller and the code responsible for fuzzy logic is completely independent of hardware and interface. All parameters of the fuzzy controller are configurable from the membership functions and rule base, even the universe of discourse of the linguistic terms of output variables. The process of testing and validating the system will use the Sun SPOT ® mobile device with J2ME code embedded controllers, which were previously generated and tuned on the proposed system. As a case study, the fuzzy controller embedded in the Sun SPOT ® will be used to control a Quanser® level system, and the graphics resultant of the tests will be presented. },
keywords = {Fuzzy, J2ME, Embedded Systems, Sun SPOT, Level Control},
language = {English},
publisher = {ABCM},
pages = {400-409}
}

Fuzzy intelligent systems are present in a variety of equipment, ranging from household appliances to small devices like digital cameras and cell phones, being used primarily for dealing with the uncertainties in the modeling of real systems, which are typically nonlinear. However, commercial implementations of fuzzy systems are not general purpose and do not have portability to different hardware platforms. Thinking about it, this paper proposes the implementation of a system capable of generating a Takagi-Sugeno fuzzy controller written in Java To Platform Micro Edition (J2ME), whose modular design makes it portable to any mobile device that supports J2ME. Thus, the proposed
development platform is capable of generating all classes of a controller and the code responsible for fuzzy logic is completely independent of hardware and interface. All parameters of the fuzzy controller are configurable from the membership functions and rule base, even the universe of discourse of the linguistic terms of output variables. The process of testing and validating the system will use the Sun SPOT ® mobile device with J2ME code embedded controllers, which were previously generated and tuned on the proposed system. As a case study, the fuzzy controller embedded in the Sun SPOT ® will be used to control a Quanser® level system, and the graphics resultant of the tests will be presented.

@conference{araujo2_2012,
title = {Java Implementation of an Intelligent System For Selection of Controllers Using the Qlearning Algorithm},
author = {Ugulino de Araújo, M.E.; de Aguiar Correia Feliciano, R.; Ugulino de Araújo, F.M.; Costa Barros, D.M.},
booktitle = {ABCM Symposium Series in Mechatronics},
year = {2012},
volume = {4},
institution = {Federal Institute of Education, Science and Technology of Paraíba, Brazil; Federal University of Rio Grande do Norte, Brazil},
abstract = { Currently PID controllers are widely used in industrial process control, but controllers which use AI techniques, such as fuzzy, neural networks and hybrid techniques, are no longer restricted to academic research. They are also gaining ground among industrial applications. However, each type of controller, depending on the tuning or training technique, presents better performance in certain regions or operation points, and that the design and implementation of these controllers frequently depends of proprietary software, which usually has a very high cost. Aiming to have an open source environment capable of tuning PI, PD or PID fuzzy controllers, while determining the best control signal for each instant and switching between those controllers, this work proposes an algorithm of reinforcement learning, named Q-learning to identify which controller is best suited to work in different linear regions of the system. It is used a soft-switching technique to switch between control signals and the integral of the error as metric for selection of the most suitable controller. For validation and testing of this proposal, it is used a system level control of Quanser, where the Q-learning algorithm is trained using the ε-greedy policy. Test results display the system switching among controllers and the comparison with each controller performing separately in order to prove the functioning and effectiveness of the proposed implementation. },
keywords = {Intelligent system, PID, Fuzzy, Q-learning, control signal soft-switching},
language = {English},
publisher = {ABCM},
pages = {410-419}
}

Currently PID controllers are widely used in industrial process control, but controllers which use AI techniques, such as fuzzy, neural networks and hybrid techniques, are no longer restricted to academic research. They are also gaining ground among industrial applications. However, each type of controller, depending on the tuning or training technique, presents better performance in certain regions or operation points, and that the design and implementation of these controllers frequently depends of proprietary software, which usually has a very high cost. Aiming to have an open source environment capable of tuning PI, PD or PID fuzzy controllers, while determining the best control signal for each instant and switching between those controllers, this work proposes an algorithm of reinforcement learning, named Q-learning to identify which controller is best suited to work in different linear regions of the system. It is used a soft-switching technique to switch between control signals and the integral of the error as metric for selection of the most suitable controller. For validation and testing of this proposal, it is used a system level control of Quanser, where the Q-learning algorithm is trained using the
ε-greedy policy. Test results display the system switching among controllers and the comparison with each controller performing separately in order to prove the functioning and effectiveness of the proposed implementation.

@conference{zhang_2010,
title = {Engineering Technology Laboratory Enhancement with LabVIEW},
author = {Zhang, Y.; Akujuobi, C.; Wang, Y.; Cui, S.},
booktitle = {2010 American Society for Engineering Education Annual Conference},
year = {2010},
institution = {Prairie View A&M University, TX, USA},
abstract = {Engineering Technology (ET) is the application of engineering principles and modern technology to help solve or prevent technical problems. The programs are designed to meet the growing need created by the technology revolution for college-educated problem solvers who can support the engineering process. Thus, the ET program is featured with its emphasis on hands-on skills training, to enable ET students to solve production and system implementation problems and help them explain solutions. Therefore, in order to cater to the industry requirements in the job market, the need for updating the educational infrastructure along with technology trend is urgent in the ET program. In response to the recognition and support of federal agencies to make progress toward a diverse, competitive and globally engaged US workforce of scientists, engineers, technologists and well prepared citizens, as well as to better fulfill its departmental primary purpose to prepare students for a successful professional career in engineering technology and related fields, authors are now collaborating on 4 external grants, including 3 from NSF and 1 from Dept of Education, to propel the curriculum development and laboratory enhancement. And this paper introduces the current progress and following implementation strategies on the undergraduate laboratory enhancement plan. },
language = {English},
publisher = {ASEE}
}

Engineering Technology (ET) is the application of engineering principles and modern technology to help solve or prevent technical problems. The programs are designed to meet the growing need created by the technology revolution for college-educated problem solvers who can support the engineering process. Thus, the ET program is featured with its emphasis on hands-on skills training, to enable ET students to solve production and system implementation problems and help them explain solutions. Therefore, in order to cater to the industry requirements in the job market, the need for updating the educational infrastructure along with technology trend is urgent in the ET program. In response to the recognition and support of federal agencies to make progress toward a diverse, competitive and globally engaged US workforce of scientists, engineers, technologists and well prepared citizens, as well as to better fulfill its departmental primary purpose to prepare students for a successful professional career in engineering technology and related fields, authors are now collaborating on 4 external grants, including 3 from NSF and 1 from Dept of Education, to propel the curriculum development and laboratory enhancement. And this paper introduces the current progress and following implementation strategies on the undergraduate laboratory enhancement plan.

@article{canureci_2010,
title = {Experimental studies on faults detection using residual generator},
author = {Canureci, G.; Vinatoru, M.; Maican, C.; Vladut, G.},
booktitle = {2010 IEEE International Conference on Automation Quality and Testing Robotics (AQTR)},
year = {2010},
institution = {University of Craiova, Romania},
abstract = {In this paper one will develop the faults detection and localization method using residual vectors, in order to emphasize the noises, disturbances and faults on the outputs L1 and L2 of the control level plant with two coupled tanks îQuanser Water Level Control Two Tank Moduleî. The proposed method was theoretically developed and experimentally verified in this plant and allowed detection and localization of two faults created in a real plant. The experiments presented were realized using Matlab Simulink program. },
keywords = {plant, fault detection method, residual generator, fault localization method, residual vector, Quanser water level control two tank module, Matlab Simulink program},
language = {English},
publisher = {IEEE}
}

In this paper one will develop the faults detection and localization method using residual vectors, in order to emphasize the noises, disturbances and faults on the outputs L1 and L2 of the control level plant with two coupled tanks îQuanser Water Level Control Two Tank Moduleî. The proposed method was theoretically developed and experimentally verified in this plant and allowed detection and localization of two faults created in a real plant. The experiments presented were realized using Matlab Simulink program.

@conference{Costa2010,
title = {Java Fuzzy Logic Toolbox for Industrial Process Control},
author = {B. J. Costa and C. G. Bezerray and L. A. de Oliveiraz},
booktitle = {XVIII Congresso Brasileiro de Automatica},
year = {2010},
abstract = {This paper describes the design, implementation and application of a fuzzy logic toolbox for in-dustrial process control based on Java language, supporting communication through the OPC industrial protocol. The toolbox is written in Java and is completely independent of any other platforms. It provides easy and func-tional tools for modelling, building and editing complex fuzzy inference systems and using such logic systems to control a large variety of industrial processes. },
keywords = {fuzzy logic, industrial process control, OPC}
}

This paper describes the design, implementation and application of a fuzzy logic toolbox for in-dustrial process control based on Java language, supporting communication through the OPC industrial protocol. The toolbox is written in Java and is completely independent of any other platforms. It provides easy and func-tional tools for modelling, building and editing complex fuzzy inference systems and using such logic systems to control a large variety of industrial processes.

@inproceedings{Currie,
title = {Lightweight Model Predictive Control intended for Embedded Applications},
author = {Currie, J. and D.I. Wilson},
booktitle = {Proceedings of the 9th International Symposium on Dynamics and Controlof Process Systems},
year = {2010},
abstract = {The computational demands of Model predictive control (MPC) are well known, and due to its internal constrained optimiser, historically has been ill-suited for embedded controllers designed to tackle high-speed applications. This paper explores the options of developing a low-cost lightweight MPC controller destined for micro-controller or FPGA architectures for modest applications demanding reasonable controller horizons. An object based MPC development tool is introduced and applied to an experimental 4-tank level system to explore the performance of the algorithm. },
keywords = {Control Applications in Chemical Processes; Process Scheduling and Control; Process Optimization}
}

The computational demands of Model predictive control (MPC) are well known, and due to its internal constrained optimiser, historically has been ill-suited for embedded controllers designed to tackle high-speed applications. This paper explores the options of developing a low-cost lightweight MPC controller destined for micro-controller or FPGA architectures for modest applications demanding reasonable controller horizons. An object based MPC development tool is introduced and applied to an experimental 4-tank level system to explore the performance of the algorithm.

@conference{Hagg2010,
title = {On Subspace Identification of Cascade Structured Systems},
author = {Hagg, P and Wahlberg B. and Sandberg H.},
booktitle = {49th IEEE Conference on Decision and Control},
year = {2010},
abstract = {In identification it is important to take a priori structural information into account in many applications, something that is difficult when using subspace methods. Here will study how to incorporate a special structure, a cascade structure with two subsystems. Two new methods are derived for estimating system with this structure. The problem when using subspace identification on cascade structured system is that the states from the first subsystem are mixed with states from the second subsystem via a unknown similarity transform. The first indirect method finds a similarity transform that takes the system back to a form such that the subsystems can be recovered. The second method uses the fact that the structure of the extended observability matrix is known for cascade systems. However, it only works when both subsystems have order one. In practice this is still a common case. The results of the two methods seem promising, as illustrated by applying the methods to a real process, the double tank process. The performance is comparable with state of the art methods. Finally the problem of optimal input design for cascade systems are introduced, and illustrated by a simple example. },
keywords = {cascade systems, control system synthesis, identification, observability, optimal control, process control}
}

In identification it is important to take a priori structural information into account in many applications, something that is difficult when using subspace methods. Here will study how to incorporate a special structure, a cascade structure with two subsystems. Two new methods are derived for estimating system with this structure. The problem when using subspace identification on cascade structured system is that the states from the first subsystem are mixed with states from the second subsystem via a unknown similarity transform. The first indirect method finds a similarity transform that takes the system back to a form such that the subsystems can be recovered. The second method uses the fact that the structure of the extended observability matrix is known for cascade systems. However, it only works when both subsystems have order one. In practice this is still a common case. The results of the two methods seem promising, as illustrated by applying the methods to a real process, the double tank process. The performance is comparable with state of the art methods. Finally the problem of optimal input design for cascade systems are introduced, and illustrated by a simple example.