Course detail

Adaptive and Optimal Control of Drives

FEKT-LARPAcad. year: 2010/2011

Basic optimal control, linear quadratic regulator, Kálmán filter, application for control of electrical drives. Principles of adaptive controllers, model refrence adaptive control (MRAC), self-tuning regulator (STR), digital realization of controllers, application to electrical drives.

Language of instruction

Czech

Number of ECTS credits

6

Mode of study

Not applicable.

Guarantor

prof. Ing. Jiří Skalický, CSc.

Department

Department of Power Electrical and Electronic Engineering (UVEE)

Learning outcomes of the course unit

To acquire knowledge of advanced control theory and apply it to control of electrical drives

Prerequisites

The subject knowledge on the Bachelor´s degree level is requested.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Teaching methods depend on the type of course unit as specified in the article 7 of BUT Rules for Studies and Examinations.

Assesment methods and criteria linked to learning outcomes

Individual project
Written and oral examination

Course curriculum

State controller
Linear quadratic regulator
Target tracking servomechanism
Discrete control and computer realization
Adaptive control
Real time parameter identification
Model reference adaptive control
Regulator design methods

Work placements

Not applicable.

Aims

To acquire knowledge of optimal and adaptive control theory with application to electrical drives

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

Computer laboratory

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Astrom, Wittenmark: Adaptive Control, Addison-Wesley
Dorato, Abdallah, Cerone: Linear-Quadratic Control, Prentice Hall
Ioannou, Jing Sun: Robust Adaptive Control, Prentice Hall
Ogata: Modern Control Engineering, Prentice Hall

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme EEKR-ML Master's

    branch ML-SVE , 1 year of study, summer semester, elective specialised

Type of course unit

 

Lecture

39 hod., optionally

Teacher / Lecturer

prof. Ing. Jiří Skalický, CSc.

Syllabus

Optimal control
Linear quadratic regulator
Target tracking servomechanism
Stochastic control
LQG regulator and Kálmán filter
Robustness design
Discrete control and computer realization
Adaptive control
Real time parameter identification
Model reference adaptive control
Self-tuning regulator
Stability and robustness of adaptive systems
Regulator design methods

Exercise in computer lab

26 hod., compulsory

Teacher / Lecturer

prof. Ing. Jiří Skalický, CSc.

Syllabus

State feedback control
LQR design
LQR with disturbance rejection
Simulation of a servomechanism
Cascade compensator for LQR
Design of a robust controller
Simulation of a robust system
System -parameter identification
Design of a MRAC
Design of a STR
Design of a gain scheduling regulator
Simulation of a system with an adaptive controller
Check of credits