The exponentially growing complexity of engineering systems, such as robotic systems, autonomous vehicles, and unmanned aerial vehicles, require sophisticated control strategies that can efficiently coordinate system operation in various environments. The traditional control design approaches present significant challenges for control engineers to keep up with the increasing complexity and changing requirements. To advance embedded control system design, a paradigm shift from traditional development approaches toward more structured, systematic methodologies that can manage the multi-domain nature of control systems is critically needed. Model-based design approach is emerging as a solution for this demand. Model-based design approach uses a system model for control system development, from requirements capture to control system design, implementation, and testing. It provides an integrated environment for design, implementation, automatic code generation, and validation, which allows early error detection and continuous testing and verification. Model-based design reduces development time and cost, delivers higher-quality control systems, and enables collaboration among the engineers with different expertise.
This paper presents a graduate-level course developed to train next generation of engineers with the skills for model-based embedded control system design. The development environment, including MATLAB/Simulink, dSPACE ConfigurationDesk, dSPACE ControlDesk, and dSPACE MicroAutobox III, is introduced. The course project, a control system for a hybrid powertrain, demonstrates the ability of students to develop a complicated control system using model-based design approach and perform validation through both Model-in-the-Loop (MIL) testing and Hardware-in-the- Loop (HIL) testing. The students’ feedback is very positive and shows that the course has prepared them well for their careers in industry and research institutions.