COURSE

ROAS6000I

Optimal Control Systems

Systems Hub / Robotics and Autonomous Systems · 3 Credits

Optimal control is an effective approach that has been widely used in robotics and autonomous systems. This course aims to provide students with a firm foundation in optimality principles in modern control systems design. Fundamental key concepts in optimal control are introduced, including Hamiltonian, Pontryagin's minimum principle, Bellman equation, dynamic programming, etc., which bring the prospect of formal linkage to reinforcement learning techniques. Different optimal control methods are also covered in this course, such as LQR, Kalman filter, LQG, MPC, etc. Additionally, the students will have the opportunity to discover and learn cutting-edge methodologies in the related field and develop the expertise in optimal control system design.