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Course module: 202000256
202000256
Learning and Adaptive Control
Course infoSchedule
Course module202000256
Credits (ECTS)5
Course typeCourse
Language of instructionEnglish
Contact persondr.ir. W.B.J. Hakvoort
E-mailw.b.j.hakvoort@utwente.nl
Lecturer(s)
Contactperson for the course
dr.ir. W.B.J. Hakvoort
Examiner
dr.ir. W.B.J. Hakvoort
Lecturer
dr. H. Koroglu, PhD
Lecturer
dr.ir. M. Vlutters
Academic year2022
Starting block
2A
Application procedureYou apply via OSIRIS Student
Registration using OSIRISYes
Aims
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.

 
Content
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.


Assessment
 
  Description
 
Test type
1 Implementation assignments Assignment(s)
2 Summary and evaluation of scientific paper Essay
3 Oral exam Oral examination
Assumed previous knowledge
Knowledge of calculus, linear algebra, linear systems, basic dynamical modelling (of mechanical systems), state-space representations, optimal control and control of MIMO systems.

Typically, the required control knowledge is obtained through one of the following courses:

- Advanced Control Engineering
- Control System Design for Mechatronics
- Control System Design for Robotics
- Optimal control
- Robust control
Participating study
Master Mechanical Engineering
Participating study
Master Systems and Control
Participating study
Master Biomedical Engineering
Participating study
Master Robotics
Required materials
Course material
Selected papers
Recommended materials
-
Instructional modes
Assessment
Presence dutyYes

Assignment
Presence dutyYes

Lecture

Self study without assistance

Tutorial

Tests
Assignment(s), Essay and oral exam

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Kies de Nederlandse taal