New Lecture at the IAT – Optimal Control and Predictive Control

Goal and Content of the Lecture

Optimal control approaches, like model predictive control, are one of the most versatile, flexible and most often used modern control approaches by now. Fields of applications span from robotics, autonomous driving, aerospace systems, energy systems, chemical processes, biotechnology, up to biomedicine. The lecture provides an introduction to fundamentals of optimal control, focusing on the method and theoretical base. It furthermore provides an outreach towards efficient numerical solution strategies and model predictive control.

Topics

• Application examples from various fields such mechatronics, robotics, electrical systems, chemical processes, economics, as well as aeronautics
• Review of nonlinear programming
• Dynamic programming, the principle of optimality, Hamilton-Jacobi-Bellman equation
• Pontryagin maximum principle
• Infinite and finite-horizon optimal control, LQ optimal control
• Numerical solution approaches for optimal control problems
• Introduction to model predictive control (MPC)

The lecture is held in English.

Further details: see TUCaN and the moodle page of the course

Click here to go to the lecture page