Course detail

Real Time Control and Simulation

FSI-RPOAcad. year: 2020/2021

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.

Language of instruction

Czech

Number of ECTS credits

Mode of study

Not applicable.

Guarantor

doc. Ing. Robert Grepl, Ph.D.

Department

Institute of Solid Mechanics, Mechatronics and Biomechanics (ÚMTMB)

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 of mathematics, kinematics, dynamics equal to previous studies and programming in Matlab/Simulink.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Lectures, computer exercises, labs.

Assesment methods and criteria linked to learning outcomes

The evaluation is based on the standard point system (0-100 points). Students can get up to 60 points for the semestral project and its presentation and up to 40 points for the final test.

Course curriculum

Not applicable.

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.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

BOLTON, W. Mechatronics: Electronic Control Systems in Mechanical Engineering. Pearson Education, 1999. 372 p. ISBN: 9780582357051.
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.
Valášek, M.: Mechatronika, skriptum ČVUT, 1995

Recommended reading

NELLES, O. Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models. Springer, 2000-12-12. 814 p. ISBN: 9783540673699.
Valášek, M.: Mechatronika, skriptum ČVUT, 1995

Elearning

eLearning: currently opened course

Classification of course in study plans

  • Programme N-MET-P Master's 1 year of study, summer semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Ing. Jan Najman, Ph.D.
doc. Ing. Robert Grepl, Ph.D.

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.
Linear, nonlinear and quadratic programming.

Laboratory exercise

26 hod., compulsory

Teacher / Lecturer

Ing. Jan Najman, Ph.D.
Ing. Matej Rajchl

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.

Elearning

eLearning: currently opened course