EE-717 / 2 credits

Teacher: Formentin Simone

Language: English

Remark: May 3rd - 7th 2021


Frequency

Only this year

Summary

This course offers an overview of direct data-driven approaches to control design. In such methods, learning tools are used to compute optimal control laws from data without relying on a model of the system. Pros and cons of direct approaches as compared to model-based design are also discussed.

Content

Note

The course will be offered in partnership with the International Graduate School on Control (IGSC) of the European Embedded Control Institute (EECI) and, therefore, will be open to external students (see http://www.eeci-igsc.eu/).

Keywords

Learning-based control, data-driven control, system identification.

Learning Prerequisites

Required courses

Fundamentals of control theory, basics of system identification.

Recommended courses

Optimal and model-predictive control.

Learning Outcomes

By the end of the course, the student must be able to:

  • Design simple and advanced control systems based on data.

Assessment methods

Oral presentation.

In the programs

  • Exam form: Oral presentation (session free)
  • Subject examined: Learning to control
  • Lecture: 21 Hour(s)

Reference week

 MoTuWeThFr
8-9     
9-10     
10-11     
11-12     
12-13     
13-14     
14-15     
15-16     
16-17     
17-18     
18-19     
19-20     
20-21     
21-22