352-0546/03 – Systems Identification and Simulation (IaSS)

Gurantor departmentDepartment of Control Systems and InstrumentationCredits5
Subject guarantorprof. Ing. Petr Noskievič, CSc.Subject version guarantorprof. Ing. Petr Noskievič, CSc.
Study levelundergraduate or graduateRequirementCompulsory
Year1Semestersummer
Study languageCzech
Year of introduction2019/2020Year of cancellation2025/2026
Intended for the facultiesFSIntended for study typesFollow-up Master
Instruction secured by
LoginNameTuitorTeacher giving lectures
NOS52 prof. Ing. Petr Noskievič, CSc.
SKU52 Ing. Jolana Škutová, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 3+2
Part-time Credit and Examination 12+4

Subject aims expressed by acquired skills and competences

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.

Teaching methods

Lectures
Tutorials
Project work

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.

Compulsory literature:

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.

Recommended 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

Way of continuous check of knowledge in the course of semester

Active work at the excercises. Projects. Combined examination.

E-learning

Other requirements

Elaboration of three projects focused on the creation of the mathematical models and simulation of mechatronic systems. Student has to be able to use numerical methods for the simulation of dynamic systems and solve identification tasks using the simulation programme MATLAB – Simulink.

Prerequisities

Subject codeAbbreviationTitleRequirement
352-0329 MaSMS Modelling and Simulation of Mechatronic Systems Recommended

Co-requisities

Subject has no co-requisities.

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. 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.

Conditions for subject completion

Full-time form (validity from: 2019/2020 Winter semester, validity until: 2025/2026 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 40 (40) 20
                Project 1 Project 10  6
                Project 2 and experimental measurement Project 15  8
                Project 3 Project 10  6
                Activity Other task type 5  0
        Examination Examination 60 (60) 22
                Written exam Written examination 30  16
                Oral exam Oral examination 30  6
Mandatory attendence parzicipation: Taking part at the exercises, processing of two projects.

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2021/2022 (N0714A270003) Mechatronics EMM P Czech Ostrava 1 Compulsory study plan
2021/2022 (N0714A270003) Mechatronics EMM K Czech Ostrava 1 Compulsory study plan
2020/2021 (N0714A270003) Mechatronics EMM P Czech Ostrava 1 Compulsory study plan
2020/2021 (N0714A270003) Mechatronics EMM K Czech Ostrava 1 Compulsory study plan
2019/2020 (N0714A270003) Mechatronics EMM P Czech Ostrava 1 Compulsory study plan
2019/2020 (N0714A270003) Mechatronics EMM K Czech Ostrava 1 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner