Dynamic Systems Identification

Garant předmětu:

Lecturer:

Tutor:

Supervisor:

Department of Instrumentation and Control Engineering

Synopsis:

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. Lectures are concentrated to the most frequent methods which are applied in practice.

Requirements:

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

Syllabus of lectures:

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

Syllabus of tutorials:

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 stochastic process

Study Objective:

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

Study materials:

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

Note:

Further information:

No time-table has been prepared for this course

The course is a part of the following study plans:

• 12 131 NSTI PRT 2012 základ (compulsory course in the program)