English

If sufficient demand

The aim of the course is to learn basic and advanced methods for control system synthesis. The PhD student should gain hands-on experience of several of the most important control design methods that have been developed within the history of control theory.

Control system design - a perspective. Requirements and fundamental limitations. Loopshaping. QFT design. Pole placement. PID design. Bottom-up design. Interaction. LQG design. Robust control, H-infinity synthesis, Glover-McFarlane.
Model predictive control. Iterative learning control. Gain scheduling and adaptive control.

know and understand simple and advanced methods for control system synthesis
know how to define control system requirements
know the fundamental limitations of what can be achieved by feedback control
understand how model uncertainty impacts control performance and know suitable control methods for systems with significant uncertainty
know different architectures and design principles for larger control systems
know how control systems can learn from measurements and successively improve their performance and adapt to changes

be able to analyze, design and implement a control system using suitable methods
be able to use numerical software (e.g. Matlab) to solve advanced synthesis problems

Lectures

Exercises

Miscellaneous

Some of the lectures consist of short presentations given by the participants.

Written assignments

Seminars given by participants

Miscellaneous

Individual exercises and handins, some in form of control design challenges.

Failed, pass

Knowledge corresponding to a basic course in control theory.

 

Lecture slides and hand-out material.

FRT155F

 -10-28

Professor Thomas Johansson