654-0929/01 – Modelling of industrial processes (MPP)

Gurantor departmentDepartment of Industrial Systems ManagementCredits10
Subject guarantordoc. Ing. Milan Heger, CSc.Subject version guarantordoc. Ing. Milan Heger, CSc.
Study levelpostgraduateRequirementChoice-compulsory type B
YearSemesterwinter + summer
Study languageCzech
Year of introduction2022/2023Year of cancellation
Intended for the facultiesFMT, HGFIntended for study typesDoctoral
Instruction secured by
LoginNameTuitorTeacher giving lectures
HEG30 doc. Ing. Milan Heger, CSc.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Examination 20+0
Part-time Examination 20+0

Subject aims expressed by acquired skills and competences

Student will be able to formulate the basic methods of simulation models realization on the digital computer, to create mathematical models of selected industrial 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 physical and mathematical modelling of industrial processes. Students are acquainted with analytical and experimental methods of identification of the mathematical description of the dynamic system and with methods necessary for implementation of the model on a digital computer. Students are introduced to artificial intelligence (fuzzy models, expert models, models of neural networks, genetic algorithms), attention is paid mainly to the models of neural networks and their application to the selected industrial processes.

Compulsory literature:

RUSSELL, S. J. and P. NORVIG. Artificial intelligence: a modern approach. 3rd ed., Pearson new international ed. Harlow: Pearson, c2014. ISBN 978-1-292-02420-2. CLOSE, Ch. M., D. K. FREDERICK a Jonathan C. NEWELL. Modeling and analysis of dynamic systems. 3rd ed. New York: Wiley, c2002. ISBN 0-471-39442-4. SAMARASINGHE, S. Neural networks for applied sciences and engineering: from fundamentals to complex pattern recognition. Boca Raton: Auerbach Publications, c2007. ISBN 978-0-8493-3375-0.

Recommended literature:

NOSKIEVIČ, P. Modelling and simulation of mechatronic systems using MATLAB Simulink. Ed. 1st. Ostrava: VŠB - Technical University of Ostrava, 2013. ISBN 978-80-248-3150-3. JANČÍKOVÁ, Z. Modelling and simulation. Ostrava: VŠB-TU Ostrava, 2015.

Way of continuous check of knowledge in the course of semester

Ústní zkouška

E-learning

Other requirements

Elaboratin of seminar work on a given topic.

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

1. Introduction to systems modelling. 2. Mathematical description of dynamic systems. 3. Physical modelling. 4. Mathematical modelling, analogy. 5. Analytical and experimental methods of system identification. 6. Simulation of systems. 7. Simulation program SIMULINK, creation of simulation models of selected industrial processes. 8. Unconventional modelling, artificial intelligence. 9. Neural networks, neuron models, learning and generalisation of neural networks, learning algorithms. 10. Creation of neural networks models of selected industrial processes in software tools NEUREX, Statistika Neural Networks and MATLAB Neural Network Toolbox.

Conditions for subject completion

Full-time form (validity from: 2022/2023 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of pointsMax. počet pokusů
Examination Examination   3
Mandatory attendence participation:

Show history

Conditions for subject completion and attendance at the exercises within ISP:

Show history

Occurrence in study plans

Academic yearProgrammeBranch/spec.Spec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2024/2025 (P0413D270002) Management of Industrial Systems P Czech Ostrava Choice-compulsory type B study plan
2024/2025 (P0413D270002) Management of Industrial Systems K Czech Ostrava Choice-compulsory type B study plan
2023/2024 (P0413D270002) Management of Industrial Systems P Czech Ostrava Choice-compulsory type B study plan
2023/2024 (P0413D270002) Management of Industrial Systems K Czech Ostrava Choice-compulsory type B study plan
2022/2023 (P0413D270002) Management of Industrial Systems P Czech Ostrava Choice-compulsory type B study plan
2022/2023 (P0413D270002) Management of Industrial Systems K Czech Ostrava Choice-compulsory type B study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner

Assessment of instruction

Předmět neobsahuje žádné hodnocení.