455-0100/01 – Knowledge Based Control Systems (ZSR)

Gurantor department	Department of Measurement and Control	Credits	4
Subject guarantor	prof. Dr. Ing. Miroslav Pokorný	Subject version guarantor	prof. Dr. Ing. Miroslav Pokorný
Study level	undergraduate or graduate	Requirement	Choice-compulsory
Year		Semester	winter
		Study language	Czech
Year of introduction	2002/2003	Year of cancellation	2002/2003
Intended for the faculties	FEI	Intended for study types	Master

Instruction secured by
Login	Name	Tuitor	Teacher giving lectures
MAT57	Ing. Martin Matušů
POK40	prof. Dr. Ing. Miroslav Pokorný

Extent of instruction for forms of study
Form of study	Way of compl.	Extent
Full-time	Credit and Examination	2+2

Subject aims expressed by acquired skills and competences

Teaching methods

Lectures
Individual consultations
Tutorials
Experimental work in labs
Project work

Summary

The aim of the course is to acquaint students with fuzzy expert systems and fuzzy controllers including its design metodology After passing the course students have the main knowledge and skills with knowledge systems and their using. Students are able to develop the fuzzy oriented expert or control system. The course is focused on the area of modern artificial intelligence methods application in the information and control systems. Introduces the complex systems modelling problems and linguistic describing of its behaviour using the experts knowledge. Basic procedures of fuzzy mathematics and fuzzy logic are presented including the fuzzy expert and fuzzy control systems development methodology. Next the course presents the principles of knowledge intelligent cotrol using the neural networks and genetic algorithms.

Compulsory literature:

Novák,V.: Fuzzy množiny a jejich aplikace, SNTL Praha, 1992. Pokorný,M.:Umělá inteligence v modelování a řízení, BEN Praha, 1996. Vysoký,P.: Fuzzy řízení, ČVUT Praha, 1996. Cox,E.: The Fuzzy Systems Handbook, Academic Press, Inc., 1994. Firemní materiály MOTOROLA. Goldberg,D.E.: Genetic Algorithms, Addison-Weslley Publishing, 1989 Novák,V.: Základy fuzzy modelování, BEN Praha, 2000

Recommended literature:

Studijní materiály pro studenty kombinovaného studia jsou k dispozici na adrese http://kat455.vsb.cz

Way of continuous check of knowledge in the course of semester

Verification of study: 90 points for elaboration of 3 written tests Conditions for credit: 10 points for elaboration of individual semestral project (expert system or fuzzy controller)

E-learning

Other requirements

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

Lectures: Complex system modelling principles using numerical and knowledge approaches. Fuzzy sets theory Uncertainty and its fuzzy representation Multivalues fuzzy linguistic logic Fuzzy linguistic models, Mamdani and Takagi-Sugeno fuzzy rules oriented models Aproximative reasoning, inference algorithms Fuzzy expert systems, design methodology, application Rule base cognitive analysis Fuzzy control, design methodology, application Fuzzy controller properties and stability Intelligent knowledge controllers, architecture and properties Neural networks in control systems Genetic algorithms in control systems Laboratories: Introduction to laboratory praxis Motion system analysis of mobile robot model VIMR Orientation system analysis of mobile robot model VIMR Motion trajectory definition and realisation in VIMR control system Communication in control system VIMR On board microprocessor VIMR control system Hierarchical control robot system VIMR using PC and HC12 Projects: Individual semestral project (expert system or fuzzy controller) Computer labs: Fuzzy procedures application using MATLAB Fuzzy linguistic models design using LMPS and NEFRIT Zadeh´s interpolation method of approximative reassoning Design of expert systems using LMPS programme system Fuzzy control mobile robot VIMR Fuzzy control development using programme system FREG Fuzzy microprocessor HC121, control system of mobile robot VIMR Neural and fuzzy neural networks development using programme systems NEUREX and FUZNET

Conditions for subject completion

Full-time form (validity from: 1960/1961 Summer semester)

Task name	Type of task	Max. number of points (act. for subtasks)	Min. number of points	Max. počet pokusů
Exercises evaluation and Examination	Credit and Examination	100 (145)	51	3
Examination	Examination	100	0	3
Exercises evaluation	Credit	45	0	3

Mandatory attendence participation:

Show history

Conditions for subject completion and attendance at the exercises within ISP:

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Occurrence in study plans

Academic year	Programme	Branch/spec.	Spec.	Form	Study language	Tut. centre	Year	Type of duty
2002/2003	(M2612) Electrical Engineering and Computer Science	(2601T004) Measurement and Control Engineering		P	Czech	Ostrava		Choice-compulsory	study plan
2002/2003	(M2612) Electrical Engineering and Computer Science	(2612T018) Electronics and Communication Technology		P	Czech	Ostrava		Choice-compulsory	study plan
2002/2003	(M2612) Electrical Engineering and Computer Science	(2642T004) Electrical Machines, Apparatus and Drives	(10) Elektrické stroje a přístroje	P	Czech	Ostrava		Choice-compulsory	study plan
2002/2003	(M2612) Electrical Engineering and Computer Science	(2642T004) Electrical Machines, Apparatus and Drives	(20) Elektrické pohony a výkonová elektronika	P	Czech	Ostrava		Choice-compulsory	study plan
2002/2003	(M2612) Electrical Engineering and Computer Science	(3902T023) Computer Science		P	Czech	Ostrava		Choice-compulsory	study plan
2002/2003	(M2612) Electrical Engineering and Computer Science	(3907T001) Electrical Power Engineering		P	Czech	Ostrava		Choice-compulsory	study plan
2002/2003	(M2612) Electrical Engineering and Computer Science	(2601T004) Measurement and Control Engineering		P	Czech	Ostrava	5	Choice-compulsory	study plan

Occurrence in special blocks

Block name	Academic year	Form of study	Study language	Year	W	S	Type of block	Block owner

Assessment of instruction

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