Course detail

Adaptive and Optimal Control of Drives

FEKT-LARPAcad. year: 2015/2016

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

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


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).


Not applicable.

Recommended optional programme components

Not applicable.


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

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).

Language of instruction


Work placements

Not applicable.

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


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

Classification of course in study plans

  • Programme EEKR-ML Master's

    branch ML-SVE , 2. year of study, winter semester, 6 credits, optional specialized

  • Programme EEKR-ML1 Master's

    branch ML1-SVE , 2. year of study, winter semester, 6 credits, optional specialized

  • Programme EEKR-CZV lifelong learning

    branch ET-CZV , 1. year of study, winter semester, 6 credits, optional specialized

Type of course unit



39 hours, optionally

Teacher / Lecturer

Exercise in computer lab

26 hours, compulsory

Teacher / Lecturer