Course detail
Real Time Control and Simulation
FSI-RPO Acad. year: 2018/2019 Summer semester
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
4
Supervisor
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.
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.
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.
The study programmes with the given course
Programme M2A-P: Applied Sciences in Engineering, Master's
branch M-MET: Mechatronics, 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.