Early in the course development process, the team at Quanser and Dr. Li decided to exclude complex modelling and mathematical methods for designing controllers. Not only those topics were taught in later courses, but by simply raising the difficulty of the technical content, Dr. Li knew students will be discouraged from pursuing controls engineering. Instead, the course was designed to use interactive simulations, Quanser’s QLabs digital twinning technology, and the Quanser QUBE Servo 2 DC motor hardware plant so students could explore key concepts of a control system, such as why the control of a simple DC motor is vital in many engineering applications.
Figure 1: Student learning image processing techniques using a camera mounted on a QUBE-Servo 2
Figure 2 outlines a series of hands-on explorations that cover core controls concepts as well as concepts related to autonomous driving, such as computer vision, IoT, and motion planning. These exploratory activities culminated in an immersive mini-PBL activity that required students to develop a vision-based ball balancer by designing the necessary controllers, rapid prototyping components, and integrating the required sensors. Most of the course activities were scaffolded in that the more complex components and subsystems were provided to students in an effort to facilitate a deeper understanding of the problem at hand, rather than spending time trying to figure out unnecessary details.
Figure 2: Laboratory excesises
A key goal throughout the course was to enhance students’ engineering literacy, which is, the process of effectively using engineering language to describe problems and use engineering principles to identify and solve complex engineering problems. Throughout the course, students were given access to state-of-the-art software tools, such as MathWork’s Simulink® and Quanser’s QUARC, as well as laboratory-grade equipment to simulate a variety of dynamical systems and analyze the experimental results.