Optimal control
Frequency
Every 2 years
Summary
This doctoral course provides an introduction to optimal control covering fundamental theory, numerical implementation and problem formulation for applications.
Content
Optimization and optimal control play pivotal roles in many engineering applications – ranging from autonomous vehicles, robotics and chemical reactors to smart girds and aeronautics. The course will cover the following topics:
Basics of optimal control theory
- Optimality conditions for static problems
- Formulation of optimal control problems
- Gateaux derivative
- Pontryagin Maximum Principle
Numerical optimal control
- Indirect methods
- Direct solution methods
- Efficient derivative computation
Advanced aspects of optimal control
- Existence of optimal solutions
- Dual variables
- Singular problems
- Dissipativity and turnpike properties
Receding-horizon control of sampled-data systems
- Sufficient stability conditions with and without terminal constraints
- Economic cost functions
- Differences of continuous time and discrete time formulations
Outlook
- Robust optimal control
- Modeling and implementation aspects
Note
Learning Outcomes
By the end of the course, the student must be able to:
- Solve control problems arising in their research projects by means of optimal control approaches.
Assessment methods
Project Report.
In the programs
- Exam form: Project report (session free)
- Subject examined: Optimal control
- Lecture: 33 Hour(s)
- Exercises: 13 Hour(s)
- Exam form: Project report (session free)
- Subject examined: Optimal control
- Lecture: 33 Hour(s)
- Exercises: 13 Hour(s)
Reference week
| Mo | Tu | We | Th | Fr | |
| 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 |
Légendes:
Lecture
Exercise, TP
Project, other