Intelligent & Adaptive Control Systems
| Title | Ευφυή και Προσαρμοστικά Συστήματα Αυτομάτου Ελέγχου / Intelligent & Adaptive Control Systems |
| Code | 114 |
| Faculty | Engineering |
| School | Electrical and Computer Engineering |
| Cycle / Level | 1st / Undergraduate |
| Teaching Period | Winter |
| Coordinator | Georgios Rovithakis |
| Common | No |
| Status | Active |
| Course ID | 600001079 |
Programme of Study: Electrical and Computer Engineering
Registered students: 30
| Orientation | Attendance Type | Semester | Year | ECTS |
|---|---|---|---|---|
| ELECTRICAL ENERGY | Elective Courses | 9 | 5 | 5 |
| ELECTRONICS AND COMPUTER ENGINEERING | Elective Courses | 9 | 5 | 5 |
| TELECOMMUNICATIONS | Elective Courses | 9 | 5 | 5 |
| Academic Year | 2022 – 2023 |
| Class Period | Winter |
| Faculty Instructors | |
| Class ID | 600218045
|
Course Type 2021
Specialization / Direction
Course Type 2016-2020
- Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
- Face to face
Digital Course Content
- e-Study Guide https://qa.auth.gr/en/class/1/600218045
- eLearning (Moodle):
Language of Instruction
- Greek (Instruction, Examination)
Prerequisites
General Prerequisites
Modeling & Simulation of Dynamical Systems
Automatic Control Systems Ι, II
Learning Outcomes
Upon successfull completion of the course, the students will be able to:
a) design and analyze adaptive controllers for linear time invariant systems,
b) understand the problems, will analyze and design neuro-adaptive controllers for uncertain nonlinear systems in Brunovsky canonical form,
c) simulate and implement adaptive controllers using MATLAB.
General Competences
- Apply knowledge in practice
- Retrieve, analyse and synthesise data and information, with the use of necessary technologies
- Work autonomously
- Advance free, creative and causative thinking
Course Content (Syllabus)
1. Introduction (problem description, examples - applications).
2. Model Reference Adaptive Control (MRAC), (direct and Indirect control schemes, with-without normalization).
3. Adaptive Pole Placement Control (APPC), (polynomial approach, state-space approach, adaptive linear quadratic control).
4. Neuroadaptive Control of Uncertain Systems.
Keywords
Adaptive Control, Neural Networks
Educational Material Types
- Notes
Use of Information and Communication Technologies
Use of ICT
- Use of ICT in Course Teaching
- Use of ICT in Communication with Students
- Use of ICT in Student Assessment
Course Organization
| Activities | Workload | ECTS | Individual | Teamwork | Erasmus |
|---|---|---|---|---|---|
| Lectures | 37 | 1.2 | |||
| Tutorial | 39 | 1.3 | |||
| Project | 50 | 1.7 | |||
| Exams | 24 | 0.8 | |||
| Total | 150 | 5 |
Student Assessment
Description
Written Examination
Oral Examination of projects
Student Assessment methods
- Written Exam with Multiple Choice Questions (Summative)
- Written Exam with Short Answer Questions (Summative)
- Oral Exams (Summative)
- Written Exam with Problem Solving (Summative)
- Report (Summative)
Bibliography
Course Bibliography (Eudoxus)
Σημειώσεις Διδάσκοντος
Additional bibliography for study
1.P.A. Ioannou, J. Sun, Robust Adaptive Control, Prentice Hall, New Jersey, 1996.
2.F.L. Lewis, S. Jagannathan, A. Yesildirek, Neural Network Control of Robot Manipulators and Nonlinear Systems, Taylor & Francis, London, 1999.
3.J.A. Farrell, M.M. Polycarpou, Adaptive Approximation Based Control, John Wiley & Sons, New Jersey, 2006.
Last Update
20-10-2022
