At the end of this course, the student is able to:
- Explain the basic concepts, assumptions, algorithms and typical applications of learning and adaptive control methods, including DOBC, ILC, AFC and MRAC
- Implement the learning and adaptive control methods and simulate their response
- Summarize and evaluate a recent development or application of learning and adaptive control methods from a literature study.
Conventionally, fixed parameter controllers are used for (motion) control. Such controllers are widely applied, because of the ease of design, stability guarantees and satisfactory performance. However, performance can often be improved significantly by updating the controller using information on the disturbance or system dynamics learned from data. Such learning and adaptive controllers are considered in this course.|
This course considers controllers that learn disturbances, particularly disturbance observer based control (DOBC) for disturbances with known dynamic behavior and iterative learning control (ILC) for repeating disturbances. Furthermore, the course considers controllers that learn the system dynamics, particularly adaptive feedforward control (AFC) learning the dynamic response to a known reference or disturbance and model adaptive reference control (MRAC) learning the controller parameters to match a prescribed closed-loop response. Furthermore extensions that require less knowledge on the control dynamics or have better generalisability are considered.
In the first part of the course, the underlying principles of the learning and adaptive control techniques are introduced and basic implementations and typical applications are presented to the students. Students also implement basic versions of the controllers in simulation. In the second part of the course, the students study and evaluate recent developments in fundamentals, algorithms and applications of learning and adaptive control techniques in literature. This can be related to a project or challenge of the students’ interest.
||Summary and evaluation of scientific paper