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System Identification
Identification de systemes dynamiques
Alireza KarimiLaboratoire d’Automatique
ME-C2 397 email:[email protected]
Site: http://la.epfl.ch, Teaching
Fall 2013
(Introduction) System Identification Fall 2013 1 / 6
Content
1. Plants, systems and models (5h c + 3h Lab )
Modeling, Type of modelsRepresentation methods
2. Nonparametric models (9h c + 6h Lab)
Time-domain methods (step and impulse response,correlation method)Frequency-domain methods (Fourier analysis, Spectralanalysis)Closed-loop identification
3. Parametric models (13h c + 6h Lab)
Linear regression (Least squares method, recursivemethods)Prediction error methodsPractical aspects (Order estimation, validation)
(Introduction) System Identification Fall 2013 2 / 6
Course Schedule
System Identification, Fall 2013Tuesday 8:15 – 11:00
Cours: BM5202 and Lab:ME A0 392Introduction
17 Sep. ModelingRepresentation methodsContinuous- and discrete-time models
24 Sep. Choice of sampling periodStep and impulse response analysis
1 Oct. IdLab1: Step and Impulse response
Auto-correlation, Cross-correlation, Random signals8 Oct. Correlation method
Excitation signal PRBSFrequency-domain methods
15 Oct. Truncation errorsMatlab demo
22 Oct. IdLab2: Correlation, PRBS
(Introduction) System Identification Fall 2013 3 / 6
Course Schedule
Spectral analysis29 Oct. Closed-loop identification
Parametric models from frequency dataLeast squares method
6 nov. Recursive least squares methodBias and variance error, Instrumental variables
12 Nov. LdLab3: Frequency-domain methods
Prediction error method19 Nov. ARX, ARMAX, OE, BJ structures
Bias and variance analysisPractical aspects
26 Nov. Order estimationValidation
3 Dec. IdLab4: Parametric Identification (CO5-CO6)
Identification en boucle fermee10 Dec. Identification Toolbox Demo
Project definition
17 Dec. IdLab5: Final Project
(Introduction) System Identification Fall 2013 4 / 6
Identification Lab
Objectives:
Practice the identificationalgorithms in simulation.
Become familiar with theIdentification Toolbox of Matlab.
Parametric identification andvalidation of the model of amechanical system.
Complete system identification(parametric and non-parametric)and validation using the realmeasured data of a
3DOF Gyroscope
3 DOF Gyroscope
(Introduction) System Identification Fall 2013 5 / 6
Course notes and Exam
Evaluation:
Brief report for each Lab (20% of the final grade).
Brief report for the final project (20% of the final grade).
Oral Exam:
1 Each student chooses 2 questions from a list of 40-50 questions.
2 He/She prepares the answer during 20 minutes.
3 He/She answers to the chosen questions (40% of the final grade).
4 He/She answers to the questions about the final project (20% of the finalgrade).
Course notes (in French):
D. Bonvin, A, Karimi, Polycopie : “Identification de systemes dynamiques”,Edition Septembre 2011.
(Introduction) System Identification Fall 2013 6 / 6
