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Lecturer(s)
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Course content
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1. Introduction to experimental identification and mathematical-physical analysis 2. Experimental identification methods, choice of input signal and model 3. Static characteristic of random process 4. Explicit solving of least square method 5. Recursive least square method 6. Extended least square method 7. Identification of multivariable systems 8. Estimation of model structure and time delay 9. Identification of nonlinear systems 10. Examples of more complicated models ? hydraulic and heat systems 11. Mechanical and electrical systems 12. Linearization, model use to control design 13. Semestral work
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Learning activities and teaching methods
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Monologic (reading, lecture, briefing), Dialogic (discussion, interview, brainstorming), Methods of individual activities, Demonstration
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Learning outcomes
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Students will be acquainted with modeling and identification of dynamic systems and they will be able to choose appropriate method and find unknown parameters.
Knowledge of experimental identification methods as the first step of control design
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Prerequisites
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Knowledge of programming environment MATLAB/SIMULINK
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Assessment methods and criteria
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Oral examination, Written examination
Active participation on seminars, tasks solution on the computer
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Recommended literature
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Dokumentace k MATLABu - MATLAB, Simulink, Control System Toolbox, Signal Processing Toolbox.
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DRÁBEK, O., MACHÁČEK, J. Experimentální identifikace (skriptum). Univerzita Pardubice, 1987.
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Dušek, František. Matlab a Simulink : úvod do používání. Pardubice: Univerzita Pardubice, 2005. ISBN 80-7194-776-8.
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