Close Help Print Course module: 202000256 202000256 Learning and Adaptive Control Course info Schedule Course module 202000256 Credits (ECTS) 5 Course type Course Language of instruction English Contact person dr.ir. W.B.J. Hakvoort E-mail w.b.j.hakvoort@utwente.nl Lecturer(s) Examiner dr.ir. W.B.J. Hakvoort Contactperson for the course dr.ir. W.B.J. Hakvoort Lecturer dr. H. Koroglu, PhD Lecturer dr.ir. M. Vlutters Academic year 2022 Starting block 2A Application procedure You apply via OSIRIS Student Registration using OSIRIS Yes 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 duty Yes Assignment Presence duty Yes Lecture Self study without assistance Tutorial Tests Assignment(s), Essay and oral exam Close Help Print