| Course label : | System modeling and control: application to robotics |
|---|---|
| Teaching departement : | EEA / Electrotechnics - Electronics - Control Systems |
| Teaching manager : | Mister ALEXANDRE KRUSZEWSKI |
| Education language : | French |
| Potential ects : | 4 |
| Results grid : | |
| Code and label (hp) : | G1G2_ED_EEA_MCS - Mod. com. syst. : app. robot |
Education team
Teachers : Mister ALEXANDRE KRUSZEWSKI / Madam SARA IFQIR / Madam SOPHIE CERF / Mister EDOUARD DAVIN / Mister Paul CHAILLOU / Mister Quentin PEYRON / Mister SALIM ZEKRAOUI / Mister YANNICK DESPLANQUES
External contributors (business, research, secondary education): various temporary teachers
Summary
This module proposes a state space model-driven methodology for the design of control algorithms. It is based on multi-physics system modeling tools for system description. The control laws produced by the techniques presented allow to go further in the control of the system than the techniques based on input-output methods (which will be briefly recalled.) i.e. physical state limits, estimation of internal variables, optimization of the control law ...
Educational goals
At the end of the course, the student will be able to: - Model and simulate a simple robotic system. - Use Matlab and Simulink for simulation, control law synthesis and validation. - Establish specifications for the control of a system with realistic constraints. - Determine the control architecture needed for trajectory tracking and system regulation multivariable. - Summarize the different correctors required. - To assimilate new theoretical notions in autonomy.
Sustainable development goals
Knowledge control procedures
Continuous Assessment
Comments: Assessment:
- 30% Project report
- 70% Continuous control (programmed written interrogations)- Understand the system control device design approach
Minimum skill set to validate the module:
- Know how to model a problem in the form of a block diagram.
- Know how to write a specification for the different controllers.
- Know how to set up a simple control solution.
- Know how to tune a PID based on the model of the system in cases of linear order system 1 and 2.
- To be able to analyze the dynamics of a looped system in the state space.
- Know the limits of the proposed controllers.
- Know the advantages of the proposed tools.
Advanced skill set to get a higher rank:
- Know how to set up and tune an extended state feedback.
- Know the interest and know how to implement a linearizing controller.
- Know the interest and know how to set up a state observer.
- Know the interest and know how to implement a feedforward scheme for trajectory tracking.
Online resources
Moodle: Matlab exercices
Pedagogy
Alterns 2h with a teacher and 2h in autonomy Based on Matlab for the computational parts Autonomy: - simple exercices - new materials (documents or videos) Teachings: - Self evaluation - feedback on the new materials - exercices with Matlab
Sequencing / learning methods
| Number of hours - Lectures : | 0 |
|---|---|
| Number of hours - Tutorial : | 0 |
| Number of hours - Practical work : | 0 |
| Number of hours - Seminar : | 34 |
| Number of hours - Half-group seminar : | 0 |
| Number of student hours in TEA (Autonomous learning) : | 24 |
| Number of student hours in TNE (Non-supervised activities) : | 0 |
| Number of hours in CB (Fixed exams) : | 0 |
| Number of student hours in PER (Personal work) : | 0 |
| Number of hours - Projects : | 0 |
Prerequisites
linear algebra differential systems
Maximum number of registrants
64