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System Identification [ LINMA2875 ]


5.0 crédits ECTS  30.0 h + 30.0 h   2q 

Teacher(s) Hendrickx Julien ;
Language English
Place
of the course
Louvain-la-Neuve
Online resources http://user.it.uu.se/~ts/sysidbook.pdf
Prerequisites

It is beneficial but not mandatory, to have followed the course INMA1731 (Stochastic Processes, estimation and prediction).

Main themes

Identical to the contents of the course

Aims The aim of this course is to enable the students to obtain a mathematical model of a dynamical process on the basis of input-output data measured on this process. Such mathematical model is typically required in order to predict, simulate or control this process. At the end of the course, the students will be able to estimate a mathematical model on the basis of input-output date; this implies estimating the mathematical structure of a model, estimating the parameters within that structure, and validating the model with respect to a pre-defined objective.
Evaluation methods - Exam at the end of the year
- Identification of a system on the basis of real input/output data (using the Matlab System Identification Toolbox, developed by L. Ljung)
- Exercises in the course of the year
Content The following material will be covered : 1. Mathematical models viewed as predictors
2. Non-parametric identification methods
3. Estimation of parametric models by Prediction Error Method
4. Frequency domain interpretation of the Prediction Error Method
5. Evaluation of the quality of an identified model (bias and variance)
6. Determination of the model structure : validation tools
7. Discussion of the design parameters in system identification : sampling period, number of data points, prefilters, choice of excitation signal, etc..
Bibliography Support :
The course is based on the two following books:
« System Identification », Torsten Söderström and Petre Stoica http://user.it.uu.se/~ts/sysidbook.pdf « System Identification - Theory for the user », Lennart Ljung, Prentice Hall, 1999.
Cycle et année
d'étude
> Master [120] in Mathematical Engineering
> Master [120] in Electrical Engineering
> Master [120] in Electro-mechanical Engineering
> Master [120] in Biomedical Engineering
Faculty or entity
in charge
> MAP


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