654-0905/02 – Identification and Modelling (IM)
| Gurantor department | Department of Industrial Systems Management | Credits | 10 |
| Subject guarantor | doc. Ing. Adam Pawliczek, Ph.D. | Subject version guarantor | doc. Ing. Adam Pawliczek, Ph.D. |
| Study level | postgraduate | Requirement | Choice-compulsory type B |
| Year | | Semester | winter + summer |
| | Study language | Czech |
| Year of introduction | 2022/2023 | Year of cancellation | |
| Intended for the faculties | FMT, HGF | Intended for study types | Doctoral |
Subject aims expressed by acquired skills and competences
Student will be able to formulate the basic methods of creation of mathematical description of dynamic systems for simulation purposes and synthesis of their control, to analyse real dynamic systems a for their mathematical description use appropriate identification methods, to formulate the basic methods of simulation models realization on the digital computer, to create mathematical models of selected real processes with aim of classic simulation programs and with artificial neural networks exploitation. Student will get an overview of the basic principles of mathematic-physical modelling, similarity and modelling and of classic and artificial intelligence methods necessary for model realization.
Teaching methods
Individual consultations
Project work
Summary
The course deals with methods of the mathematical description of systems creation for the purpose of synthesis of their control. Methods of mathematical-physical analysis and methods of experimental identification are discussed. Attention is paid to the deterministic ways of identification and to identification with the random course of the input variables of the identified systems. The conclusion of the course is devoted to the basics of stochastic modelling and to the basic statistical methods of the system identification.
Compulsory literature:
Recommended literature:
Way of continuous check of knowledge in the course of semester
E-learning
Other requirements
Elaboration of seminar work on a given topic.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
1. Identification in the knowledge and control process.
2. Methods of identification, a priori and a posteriori information about the identified system. Identification of structure and system parameters.
3. Identification by the method of mathematical-physical analysis.
4. Experimental identification methods. Deterministic and stochastic methods of identification.
5. System modelling by type of similarity (mathematical, physical, mathematical-physical, cybernetic).
6. Classification of models according to different aspects.
7. Principle and general description of equation and block-oriented simulation programs.
8. Model verification and simulation experiment.
9. Unconventional modelling - artificial intelligence (fuzzy models, expert models, models of neural networks, genetic algorithms).
10. Models of neural networks. Utilization of neural networks for selected technological processes modelling.
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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