Study programme 2023-2024 | Français | ||
Optimal Control and Estimation | |||
Programme component of Master's in Electrical Engineering (MONS) (day schedule) à la Faculty of Engineering |
Code | Type | Head of UE | Department’s contact details | Teacher(s) |
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UI-M1-IRELEC-022-M | Compulsory UE | VANDE WOUWER Alain | F107 - Systèmes, Estimation, Commande et Optimisation |
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Language of instruction | Language of assessment | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Credits | Weighting | Term |
---|---|---|---|---|---|---|---|---|---|
| Anglais | 32 | 16 | 0 | 0 | 0 | 4 | 4.00 | 2nd term |
AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
---|---|---|---|---|---|---|---|---|
I-SECO-030 | Optimal Control | 16 | 8 | 0 | 0 | 0 | Q2 | 50.00% |
I-SECO-031 | Optimal Estimation | 16 | 8 | 0 | 0 | 0 | Q2 | 50.00% |
Programme component |
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Objectives of Programme's Learning Outcomes
Learning Outcomes of UE
master the basic concepts of optimal control and filtering;
design linear quadratic regulators (LQR);
investigate more general problems, i.e. nonlinear systems and objective functions expressed in a general form possibly including constraints, that can be solved using Pontryagin Maximum Principle or dynamic programming;
use dynamic optimization and model predictive control algorithms;
understand the stochastic description of dynamic systems and optimal filtering, Kalman filtering and its several extensions, as well as receding-horizon observers;
work on various applications.
UE Content: description and pedagogical relevance
linear quadratic regulator; Pontryagin maximum principle; dynamic programming; dynamic optimization and model predictive control; observability of linear and nonlinear systems; stochastic system representation; Kalman filtering and extensions; receding-horizon observers; exercises.
This teaching unit deals with optimal methods, the control problem (AA Optimal Control) and the state estimation (AA Optimal Estimation). These methods complement each other to form a control strategy comprising an optimal regulator and an optimal state estimator.
Prior Experience
Not applicable
Type of Teaching Activity/Activities
AA | Type of Teaching Activity/Activities |
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I-SECO-030 |
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I-SECO-031 |
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Mode of delivery
AA | Mode of delivery |
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I-SECO-030 |
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I-SECO-031 |
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Required Learning Resources/Tools
AA | Required Learning Resources/Tools |
---|---|
I-SECO-030 | Not applicable |
I-SECO-031 | Not applicable |
Recommended Learning Resources/Tools
AA | Recommended Learning Resources/Tools |
---|---|
I-SECO-030 | Not applicable |
I-SECO-031 | Not applicable |
Other Recommended Reading
AA | Other Recommended Reading |
---|---|
I-SECO-030 | Not applicable |
I-SECO-031 | Not applicable |
Grade Deferrals of AAs from one year to the next
AA | Grade Deferrals of AAs from one year to the next |
---|---|
I-SECO-030 | Authorized |
I-SECO-031 | Authorized |
Term 2 Assessment - type
AA | Type(s) and mode(s) of Q2 assessment |
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I-SECO-030 |
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I-SECO-031 |
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Term 2 Assessment - comments
AA | Term 2 Assessment - comments |
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I-SECO-030 | Oral examination relative to exercises (with written preparation) and theory (the exam score represents 80% of the global score). Evaluation in relation to practical work sessions (20% of the global score) |
I-SECO-031 | Oral examination relative to exercises (with written preparation) and theory (the exam score represents 80% of the global score). Evaluation in relation to practical work sessions (20% of the global score) |
Term 3 Assessment - type
AA | Type(s) and mode(s) of Q3 assessment |
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I-SECO-030 |
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I-SECO-031 |
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Term 3 Assessment - comments
AA | Term 3 Assessment - comments |
---|---|
I-SECO-030 | Oral examination relative to exercises (with a written preparation) and theory (this exams represents 80% of the global score) |
I-SECO-031 | Oral examination relative to exercises (with a written preparation) and theory (this examen représents 80% of the global score). |