Optimal and Robust Control
BE3M35ORR + B3M35ORR + BE3M35ORC
This course is part of an already archived semester and is therefore read-only.
Overall learning goals
Completion requirements
- Design an LQ-optimal controller in various settings and some extensions: discrete-time vs. continuous-time, feedback vs. feedforward, finite time horizon vs. infinite time horizon, free final state vs fixed final state, regulation vs tracking of reference signal, LQG, Loop Transfer Recovery (LTR), H2-optimal control.
- Design and implement an MPC controller. For the implementation use either your own (simple) QP solver or use one of the available code generators.
- Design an optimal reference trajectory for a nonlinear dynamical system using numerical optimization.
- Model the uncertainty in a mathematical model of a dynamical system in the frequency-domain model and analyze the robustness (of stability and/or performance) of the closed-loop system with respect to this uncertainty.
- Design a controller by minimizing the Hinf system norm. Various variants: mixed-sensitivity minimization, robust Hinf-optimization based loopshaping, mu synthesis.
- Analyze the achievable control performance of a given LTI system (SISO and MIMO).
- Reduce the order of an LTI model. Reduce the order of a feedback controller.
Last modified: Wednesday, 17 February 2021, 6:04 PM