Course detail
Control Theory
FSI-VVFAcad. year: 2019/2020
The course is aimed to modern methods in design and synthesis of control circuits using methods of artificial intelligence. Presented are selected methods of artificial intelligence, optimal and adaptive methods of control, fuzzy control and neural controller. Students will adopt theoretical and practical implementation of these methods and RT control. The course broadens knowledge of specific parts of applied informatics in the field of advanced control. Used is the most advanced software and hardware technology of companies B&R Automation and Mathworks (Matlab/Simulink) and substantial know-how of course's authors.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Learning outcomes of the course unit
Analysis and design of modern feedback control systems. Students will obtain the basic knowledge of optimal control, adaptive control, fuzzy control and ANN control.
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
Recommended optional programme components
Prerequisites and corequisites
Basic literature
Levine, W.S. (1996) : The Control Handbook, CRC Press, Inc., Boca Raton, Florida 1996 , ISBN 0-8493-8570-9
Morris,K.: Introduction to Feedback Control, Academic Press, San Diego, California 2002.
Nguyen, H.T., Prasad, N.R., Walker, C.L., Walker, E.A. A First Course in Fuzzy and Neural Control. Chapman & Hall/CRC 2002.
Vegte, V.D.J.: Feedback Control Systems, Prentice-Hall, New Jersey 1990, ISBN 0-13-313651-5
Recommended reading
Nguyen, H.T., Prasad, N.R., Walker, C.L., Walker, E.A. A First Course in Fuzzy and Neural Control. Chapman & Hall/CRC 2002.
Švarc,I.:: Automatizace-Automatické řízení, skriptum VUT FSI Brno, CERM 2002, ISBN 80-214-2087-1
Zelinka Ivan, Oplatková Zuzana, Šeda Miloš, Ošmera Pavel, Včelař František; Evoluční výpočetní techniky - principy a aplikace; BEN - technická literatura, Praha 2009; ISBN 978-80-7300-218-3
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
Block 1: Physical nature of regulation
Block 2: PID controller (continuous and discrete, andi-windup, bumpless switching, advanced structural modifications)
Block 3: Identification of dynamic systems, Adaptive control and regulation (self-adjusting controller, possibilities of artificial intelligence, recursive least squares methods, regression model, controllers based on the field placement method).
Block 4: Optimal Control and Automatic Control Algorithm Generation (Applied Grammar Evolution, Genetic Programming, Nonlinear Optimization Methods)
Block 5: Fuzzy controllers (theory of fuzzy sets, principles of inference, fuzzification and defuzzification, PI / PD / PID controllers, standardized universe forms, fuzzy supervisor, fuzzy switch, fuzzy controller with multiple inputs).
Computer-assisted exercise
Teacher / Lecturer
Syllabus
2C: Optimization of PID controller parameters (classical and modern approaches).
3C: Automatic generation of control law (algorithms).
4C: Identification of dynamic systems (non-parametric methods).
5C: Identification of dynamic systems (parametric methods).
6C: Fuzzy Controller.
7C: Neural Controller.
Laboratory exercise
Teacher / Lecturer
Syllabus
2-3L: Project: Automation Studio and B+R Automation (Thermal Control / Drive Control)
4-5L: Project: D-Space (Magnetic Levitation / Helicopter / Platform Stabilization)
6L: Final project presentations.