System Identification

Garant předmětu:

Přednášející:

Cvičící:

Předmět zajišťuje:

ústav přístrojové a řídící techniky

Anotace:

The subject is aimed to explanation of basic identification methods to obtain mathematical description of deterministic and stochastic systems. Experimental identification methods are explained for linear stochastic and deterministic dynamic systems in greater detail. Analytic identification is applied for several examples and compared to experimental identification. During this course the mathematical background of system identification in both time domain and frequency domain is given. Lectures are concentrated to the most frequent methods which are applied in practice. It is expected prior experience with Matlab.

Požadavky:

It is expected prior knowledge of basic control engineering and experience with Matlab.

Osnova přednášek:

1. Fundamental terms of identification;

2. Analytic and experimental identification;

3. Model classification, parametric and nonparametric models;

4. Experimental identification with deterministic signals;

5. Parameterization of step, impulse and frequency characteristics;

6. Fundamental terms from probability and stochastic processes;

7. System identification in frequency domain and time domain;

8. Least squares methods;

9. Models ARMA, AR, MA,ARX, OE, ARMAX, BJ;

10. Prediction Error Method;

11. Maximum Likelihood Method;

12. Identification in closed loop.

Osnova cvičení:

Solution of 3 projects which are aimed at

1) analytical identification

2) structure and parameter estimation of linear process through the use of deterministic input signal

3) experimental identification of a stochastic system

Cíle studia:

After this course the student must be able to identify from recorded signal an unknown system describable with a linear time invariant model.

Studijní materiály:

L.Ljung: System Identification - Theory for User, Prentice Hall PTR, 1999.

D.E.Sebotg, T.F.Edgar, D.A.Mellichamp: Process Dynamics and Control, John Wiley & Sons,1989.

Zhu Y.C.: Multivariable System Identification for Process Control, Pergamon, Oxford, 2001.

Söderström T., Stoica P.: System Identification. Prentice Hall International, London, 2001.

Hsu H.P.: Probability, Random Variables nad Random Processes, McGraw-Hill, New York, 1996.

Hofreiter M.: Identifikace systémů I, ČVUT v Praze, Praha, 2009.

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