LJUNG,L. & GLAD,T. Modeling of Dynamic Systems.Prentice Hall,Inc.Engelwood Cliffs, New Persey 07632. ISBN 0-13-597097-0.
CLOSE, M.,Ch. & FREDERICK, K. Modeling and Analysis of Dynamic Systems. John Wiley & Sons, Inc. New York. 1995. ISBN 0-471-125172-2.
Systems Identification and Simulation
| Type of study | Follow-up Master |
|---|---|
| Language of instruction | Czech |
| Code | 352-0546/05 |
| Abbreviation | IaSS |
| Course title | Systems Identification and Simulation |
| Credits | 5 |
| Coordinating department | Department of Control Systems and Instrumentation |
| Course coordinator | prof. Ing. Petr Noskievič, CSc. |
Subject syllabus
1. Basic mathematical models of the dynamic systems, methods of their obtaining, overview of the analytical and experimental methods of system identification.
2. Experimental identification using the deterministic signals. Approximation of the step responses.
3. Parameterization of the system characteristics, area methods, integration methods.
4. Bode plot characteristic – measurement and evaluation.
5. Statistic identification methods. Statistic characteristics, stationary, random process.
6. Identification using the correlation methods. Stochastic formulation of the dynamic systems, random test signals.
7. Identification using the parameter estimation, structure of the stochastic process and system.
8. Model parameter estimation, least square methods.
9. Recursive methods of the identification, weight coefficients, exponential filtering.
10. Polynomial and nonlinear models discrete models identification. Identification of the systems operating in closed loop.
11. Realization of the simulation models, numerical solution of the differential equations, stability of the methods of the numerical solution, Stiff systems.
12. Model order reduction.
13. Software support of the identification and simulation methods.
14. Identification and simulation experiment, case study – the use of the simulation models by the design of the mechatronic system.
2. Experimental identification using the deterministic signals. Approximation of the step responses.
3. Parameterization of the system characteristics, area methods, integration methods.
4. Bode plot characteristic – measurement and evaluation.
5. Statistic identification methods. Statistic characteristics, stationary, random process.
6. Identification using the correlation methods. Stochastic formulation of the dynamic systems, random test signals.
7. Identification using the parameter estimation, structure of the stochastic process and system.
8. Model parameter estimation, least square methods.
9. Recursive methods of the identification, weight coefficients, exponential filtering.
10. Polynomial and nonlinear models discrete models identification. Identification of the systems operating in closed loop.
11. Realization of the simulation models, numerical solution of the differential equations, stability of the methods of the numerical solution, Stiff systems.
12. Model order reduction.
13. Software support of the identification and simulation methods.
14. Identification and simulation experiment, case study – the use of the simulation models by the design of the mechatronic system.
Literature
Advised literature
Soederstroem,T.-Stoica, P.: System identification Prentice Hall Int. ISBN 0-13-127606-9.
NOSKIEVIČ, P.: Modelling and Simulation of Mechatronic Systems using MATLAB-Simulink. Studijní texty v angličtině, Fakulta strojní, VŠB-TU Ostrava, 2013, 85 stran. ISBN 978-80-248-3250-3
NOSKIEVIČ, P.: Modelling and Simulation of Mechatronic Systems using MATLAB-Simulink. Studijní texty v angličtině, Fakulta strojní, VŠB-TU Ostrava, 2013, 85 stran. ISBN 978-80-248-3250-3