5.00 credits
30.0 h + 30.0 h
Q1
Teacher(s)
Bianchin Gianluca;
Language
English
> French-friendly
> French-friendly
Prerequisites
Notions of signals and systems as taught in LEPL1106.
Main themes
Development of mathematical models for linear dynamical systems (state-space representation, transfer functions) allowing to represent the dynamics in a unified way for a diversity of engineering applications (e.g. electromechanical, mechanical, electrical, chemical, biological, computer science)
Design of control schemes that meet specifications related to stability, transient and steady state performance (accuracy), and robustness. PI and PID controllers, Linear Quadratic Control, Smith predictor, feedforward control, cascade control. Use of software to design controllers.
Design of control schemes that meet specifications related to stability, transient and steady state performance (accuracy), and robustness. PI and PID controllers, Linear Quadratic Control, Smith predictor, feedforward control, cascade control. Use of software to design controllers.
Learning outcomes
At the end of this learning unit, the student is able to : | |
| 1 | With respect to the referentiel AA, this courses contributes to the development, the acquisition and the evaluation of the following learning outcomes :
|
Content
Part 1 - Analysis of systems using frequency-domain tools: Laplace transforms, dynamic response, transfer functions, system poles, block diagrams, stability, PID control, Bode and Nyquist diagrams, lead and lag compensators.
Part 2 - Analysis of systems using time-domain tools: state-space models, matrix exponentials, linearization, linear time-varying systems, Lyapunov stability, controllability and observability, pole placement, advanced control via state feedback.
Part 2 - Analysis of systems using time-domain tools: state-space models, matrix exponentials, linearization, linear time-varying systems, Lyapunov stability, controllability and observability, pole placement, advanced control via state feedback.
Teaching methods
Learning will be based on lectures (in presence mode or in distance mode) interlaced with exercise sessions (offered in class with the support of TAs) and laboratory sessions (to be realized in the laboratory room by groups of 2-4 students using laboratory equipment and MATLAB Simulink).
Evaluation methods
- Exam (75% of the final grade)
- Laboratory evaluation during the course semester (25% of the final grade)
- Other activities, such as quizzes and homework exercises, can be taken into account to compose the final grade
- In case the written exam is taken in the second session, the laboratory exam cannot be retaken and the grade remains unchanged. The laboratory grade cannot be carried over from previous years
Other information
The main language used during lectures, exercise sessions, and the laboratory is English. Examinations can be made French-friendly, upon request.
Online resources
Bibliography
J. P. Hespanha, "Linear systems theory," Princeton University Press, 2018 (available in the library)
G. F. Franklin, J. D. Powell, E. Emami-Naeini, "Feedback control of dynamic systems," Prentice Hall, 2019 (available in the library)
G. F. Franklin, J. D. Powell, E. Emami-Naeini, "Feedback control of dynamic systems," Prentice Hall, 2019 (available in the library)
Teaching materials
- Slides, notes, and laboratory manuals provided by the instructor
- Suggested readings from the referenced books
Faculty or entity
MAP
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Learning outcomes
Specialization track in Biomedical Engineering
Minor in Applied Mathematics
Master [120] in Chemical and Materials Engineering
Specialization track in Applied Mathematics
Master [120] in Mechanical Engineering
Master [120] in Electrical Engineering
Master [120] in Electro-mechanical Engineering
Master [120] in Energy Engineering
Mineure Polytechnique