Study programme 2022-2023 | Français | ||
Nonlinear system modeling and data-driven techniques applied to biological systems | |||
Programme component of Master's in Electrical Engineering : Specialist Focus on Data Science for Dynamical Systems (MONS) (day schedule) à la Faculty of Engineering |
Code | Type | Head of UE | Department’s contact details | Teacher(s) |
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UI-M2-IRELBS-003-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, Français | 36 | 24 | 0 | 0 | 0 | 5 | 5.00 | 1st term |
AA Code | Teaching Activity (AA) | HT(*) | HTPE(*) | HTPS(*) | HR(*) | HD(*) | Term | Weighting |
---|---|---|---|---|---|---|---|---|
I-SECO-108 | Nonlinear system modeling and data-driven techniques applied to biological systems | 36 | 24 | 0 | 0 | 0 | Q1 | 100.00% |
Programme component | ||
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UI-M2-IRELBS-002-M Optimal Control and Estimation |
Objectives of Programme's Learning Outcomes
Learning Outcomes of UE
discover nonlinear dynamic models in ecology and biotechnology;
implement numerical simulators of dynamic systems;
review system modeling and parameter identification techniques, with the concern of taking several sources of uncertainties into account;
use neural networks to build black-box and hybrid models of biological systems;
learn how to use asymptotic observers;
discover nonlinear feedback control techniques, either based on a dynamic model, or on the contrary model free.
UE Content: description and pedagogical relevance
introduction to population models; macroscopic models of bioprocesses; numerical simulation of dynamic systems; parameter identification (linear and nonlinear problems, least squares and maximum likelihood); introduction to neural networks for modeling and monitoring; state estimation by asymptotic observers; introduction to control of bioreactors (linearizing feedback control, extremum seeking); exercises.
Prior Experience
state space equations, observers
Type of Teaching Activity/Activities
AA | Type of Teaching Activity/Activities |
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I-SECO-108 |
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Mode of delivery
AA | Mode of delivery |
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I-SECO-108 |
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Required Learning Resources/Tools
AA | Required Learning Resources/Tools |
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I-SECO-108 | Not applicable |
Recommended Learning Resources/Tools
AA | Recommended Learning Resources/Tools |
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I-SECO-108 | Not applicable |
Other Recommended Reading
AA | Other Recommended Reading |
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I-SECO-108 | G. Bastin, D. Dochain, "On-line Estimation and Adaptive Control of Bioreactors", Elsevier, 1990 |
Grade Deferrals of AAs from one year to the next
AA | Grade Deferrals of AAs from one year to the next |
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I-SECO-108 | Authorized |
Term 1 Assessment - type
AA | Type(s) and mode(s) of Q1 assessment |
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I-SECO-108 |
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Term 1 Assessment - comments
AA | Term 1 Assessment - comments |
---|---|
I-SECO-108 | The exam relates to the understanding of the subjects of the course. It consists of an oral interview. |
Resit Assessment - Term 1 (B1BA1) - type
AA | Type(s) and mode(s) of Q1 resit assessment (BAB1) |
---|---|
I-SECO-108 |
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Term 3 Assessment - type
AA | Type(s) and mode(s) of Q3 assessment |
---|---|
I-SECO-108 |
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Term 3 Assessment - comments
AA | Term 3 Assessment - comments |
---|---|
I-SECO-108 | The exam relates to the understanding of the subjects of the course. It consists of an oral interview. |