Course detail

Adaptive and Optimal Control of Drives

FEKT-LARPAcad. year: 2019/2020

State control of electrical drives, state control with an observer, state control of servodrives, discrete state control,
basic optimal control, linear quadratic regulator, 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

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

Passed student is qualified:
- to describe structure electrcal controlled drives
- to derive state space equations of an electrical drive
- to design structure of control circuits for speed control and position control
- to design state controller
-to design linear quadratic controller

Prerequisites

Student's necessary prerequisities are knowledge of mathematics (differential equations, Laplace transform), of control theory (transfer functions, stability of feedback systems, methods how to design contrllers), of electrical machines (principle, static characteristics) and of power electronics (thyristor controlled rectifiers and transistor switch mode converters).

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Numeric and computer excersises obtain idividual projects of controlled electrical drives, projects are itrodused inthe e- learning.
To get credit it is necessary to put into e- learning all projects

Assesment methods and criteria linked to learning outcomes

Student obtains: max 15 points for numeric excersises, max. 15 points for laboratory excersises and max 70 points for final examination: written part (45 points) and oral part (25 points).

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

The goal of the subject is to acquire knowledge of linear state feedback control, optimal and adaptive control with applications to electrical drives

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

Computer laboratory is mandatory
Elaborated numeric excesises are mandatory
Compensation of an absence at laboratory after lecturer's recommendat

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

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

VUT

Faculties

University Institutes

Parts

Adaptive and Optimal Control of Drives

Type of course unit