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Systems Identification and Simulation

* Exchange students do not have to consider this information when selecting suitable courses for an exchange stay.

Course Unit Code352-0546/03
Number of ECTS Credits Allocated5 ECTS credits
Type of Course Unit *Compulsory
Level of Course Unit *Second Cycle
Year of Study *First Year
Semester when the Course Unit is deliveredSummer Semester
Mode of DeliveryFace-to-face
Language of InstructionCzech
Prerequisites and Co-Requisites
PrerequisitiesCourse Unit CodeCourse Unit Title
352-0329Modelling and Simulation of Mechatronic Systems
Name of Lecturer(s)Personal IDName
NOS52prof. Ing. Petr Noskievič, CSc.
Summary
The subject System Identification and Simulation is focused on the experimental identification of the dynamic systems and on the realization of the mathematical models of the dynamic systems using computer simulation. The methods for the model parameterization using different testing signals – step input, ramp signal, general input signal, random signal are explained after the summary of the used basic forms of the mathematical models in the time and frequency domain, continues and discrete models. The second part of the of subject is focused on the numerical methods used by the realization of the mathematical models on the digital computers. The curve fitting methods – approximation, interpolation, next numerical integration, numerical derivation and numerical methods for the solution of the differential equation – initial value problems, including of the conditions for their use and numerical stability of the obtained solution.
Learning Outcomes of the Course Unit
The practical use of the experimental identification methods, realization of the mathematical models using the simulation programmes and numerical methods implemented in the simulation programmes are the main learning outcomes of the subject.
The student is able to design the identification experiment and make a decision about the use of the identification methods based on the use of the deterministic or stochastic input signal, is able to choice a method for the evaluation of the response and parameterization of the used model. Student is able to use the methods for the identification of the discrete models of the systems.
The student is able to create the models in the simulation programmes, set up the simulation conditions and parameters, knows the basic numerical methods and their use by the simulation of the dynamic systems. He is able to analyse the dynamics of the identified systems using the mathematical models.
Course Contents
1. Basic mathematical models of the dynamic systems, methods of their obtaining, overview of the analytical and experimental methods of system identification.
2. Realization of the mathematical models, simulation programmes, their classification and use.
3. Experimental identification using the deterministic signals. Approximation of the step responses.
4. Parameterization of the system characteristics, area methods, integration methods.
5. Bode plot characteristic – measurement and evaluation.
6. Statistic identification methods. Statistic characteristics, stationary, random process.
7. Identification using the correlation methods. Stochastic formulation of the dynamic systems, random test signals.
8. Identification using the parameter estimation, structure of the stochastic process and system.
9. Model parameter estimation, least square methods.
10. Recursive methods of the identification, weight coefficients, exponential filtering.
11. Identification of the systems operating in closed loop.
12. Realization of the simulation models, numerical solution, stability of the methods of numerical solution.
13. Model order reduction.
14. Simulation experiment, case study – the use of the simulation models by the design of the mechatronic system.
Recommended or Required Reading
Required Reading:
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.
NOSKIEVIČ, P. Simulace systémů. Ostrava: VŠB-TU Ostrava, 1996. ISBN 80-7078-112-2.
NOSKIEVIČ, P. Modelování a identifikace systémů. 1. vyd. Ostrava : MONTANEX, a. s., 1999. 276 s. ISBN 80-7225-030-2.
Noskievič, P.: Modelování a simulace mechatronických systémů pomocí programu MATLAB-Simulink.VŠB-TU Ostrava, 83 stran, 2013, ISBN 978-80-248-3231-9.
Recommended Reading:
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
Hofreiter, M.: Identifikace systémů I. ČVUT v Prazem Česká technika - nakladatelství ČVUT. ISBN 978-80-01-04228-1.
Planned learning activities and teaching methods
Lectures, Tutorials, Project work
Assesment methods and criteria
Task TitleTask TypeMaximum Number of Points
(Act. for Subtasks)
Minimum Number of Points for Task Passing
Credit and ExaminationCredit and Examination100 (100)51
        CreditCredit40 (40)20
                Project 1Project10 6
                Project 2 and experimental measurement Project15 8
                Project 3Project10 6
                ActivityOther task type5 0
        ExaminationExamination60 (60)22
                Written examWritten examination30 16
                Oral examOral examination30 6