Course detail

Real Time Control and Simulation

FSI-RPOAcad. year: 2019/2020

Students will learn about advanced techniques of real-time simulations, identification, advanced control systems and state/parameter estimation. Theoretical findings will be applied on team project dealing with complex control design for real educational model.

Learning outcomes of the course unit

Students will gain knowledge about
• rapid control prototyping and HIL
• system identification
• state space control
• Kalman filter
• nonlinear control
• complex team project.

Prerequisites

Knowledge from modules: RMW, RDO, RKD.

Co-requisites

Not applicable.

Recommended optional programme components

Not applicable.

Recommended or required reading

Valášek, M.: Mechatronika, skriptum ČVUT, 1995
Valášek, M.: Mechatronika, skriptum ČVUT, 1995
Grepl, R.: Modelování mechatronických systémů v Matlab/SimMechanics, BEN - technická literatura, ISBN 978-80-7300-226-8
NELLES, O. Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models. Springer, 2000-12-12. 814 p. ISBN: 9783540673699.
BOLTON, W. Mechatronics: Electronic Control Systems in Mechanical Engineering. Pearson Education, 1999. 372 p. ISBN: 9780582357051.
NELLES, O. Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models. Springer, 2000-12-12. 814 p. ISBN: 9783540673699.

Planned learning activities and teaching methods

Lectures, labs.

Assesment methods and criteria linked to learning outcomes

Module is graded according to:
• active participation on exercises/labs
• project
• tests.

Language of instruction

Czech

Work placements

Not applicable.

Aims

Students will learn about advanced techniques of real-time simulations and related SW and HW. Theoretical findings will be demonstrated on process of identification and design of advanced control system for real laboratory model.

Specification of controlled education, way of implementation and compensation for absences

Attendance at practical training is obligatory. Evaluation are made on exercises based on evaluation criteria.

Classification of course in study plans

  • Programme M2A-P Master's

    branch M-MET , 1. year of study, summer semester, 4 credits, compulsory

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

Syllabus

Dynamic behaviour and properties of drive systems.
Structure of drive systems.
Interactive drive systems.
Basic drive systems: machines, gearbox - industry machines.
Basic drive systems: machines, gearbox - industry machines.
Operating states of drive systems and their stability.
Operating states of drive systems and their stability.
Computational modelling of drive systems.
Computational modelling of drive systems.
Stability of drive systems and defects.
Experimental monitoring of drive systems dynamics properties.

labs and studios

26 hours, compulsory

Teacher / Lecturer

Syllabus

Dynamics of rotating bodies.
Examples of drive systems structual analyses.
Basic features of torsion systems - examples.
Machines characteristics - examples.
Dynamics of gearbox systems - examples.
Dynamic properties modelling of industry machines.
Examples of drive systems control.
Computational modelling of movement systems.
Computational modelling of movement systems.
Stability of drive systems - examples.
Graded course-unit credit.

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