 | Study programme 2019-2020 | Français | |
| Optimal Control and Estimation | |||
Learning Activity |
| Code | Lecturer(s) | Associate Lecturer(s) | Subsitute Lecturer(s) et other(s) | Establishment |
|---|---|---|---|---|
| I-AUTO-106 |
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| Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term |
|---|---|---|---|---|---|---|---|
| Anglais | Anglais | 32 | 16 | 0 | 0 | 0 | Q1 |
| Organisational online arrangements for the end of Q3 2019-2020 assessments (Covid-19) |
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| Description of the modifications to the Q3 2019-2020 online assessment procedures (Covid-19) |
| The exam relates to the understanding of the subjects of the course, both the theoretical concepts as well as the numerical applications and the exercises. The examination consists of a questionnaire (with written preparation) and an oral interview. |
Content of Learning Activity
linear quadratic regulator (discrete and continuous time versions); Pontryagin maximum principle; introduction to dynamic programming; dynamic optimization and model predictive control (basic algorithms); stochastic system representation; Kalman filtering; exercises.
Required Learning Resources/Tools
Not applicable
Recommended Learning Resources/Tools
Not applicable
Other Recommended Reading
Arthur Gelb, Applied Optimal Estimation, MIT Press 1974
Mode of delivery
- Face to face
Type of Teaching Activity/Activities
- Cours magistraux
- Conférences
- Travaux pratiques
- Travaux de laboratoire
- Exercices de création et recherche en atelier
- Projet sur ordinateur
- Etudes de cas
Evaluations
The assessment methods of the Learning Activity (AA) are specified in the course description of the corresponding Educational Component (UE)
(*) HT : Hours of theory - HTPE : Hours of in-class exercices - HTPS : hours of practical work - HD : HMiscellaneous time - HR : Hours of remedial classes. - Per. (Period), Y=Year, Q1=1st term et Q2=2nd term