Intelligent Control Systems (FSI-RIR)

Academic year 2022/2023
Supervisor: Ing. Jiří Kovář, Ph.D.  
Supervising institute: ÚVSSR all courses guaranted by this institute
Teaching language: Czech
Aims of the course unit:
The goal is to master the basic design methodologies of state controllers and fuzzy controllers.
Learning outcomes and competences:
Students will learn basics of these methodologies.
Prerequisites:
The orientation in basic knowledge of dynamic systems and classic controller design methodology is supposed. The orientation in control theory and fuzzy logic is suggested.
Course contents:
The course gives a brief overview of selected parts of control theory with accent on their practical application. An applicability of introduced resources to tasks of technical systems and processes control is discussed.
Teaching methods and criteria:
The course is taught through lectures explaining the basic principles and theory of the discipline. Exercises are focused on practical topics presented in lectures.
Assesment methods and criteria linked to learning outcomes:
Course-unit credit is conferred on the base of active participation assessment in seminars and results of written test with four questions. The evaluation is fully in competence of a tutor according to the valid directives of BUT.
Controlled participation in lessons:
The attendance at lectures is recommended while at seminars it is obligatory. Education runs according to week schedules. The form of compensation of missed seminars is fully in the competence of a tutor.
Type of course unit:
    Lecture  13 × 2 hrs. optionally                  
    Computer-assisted exercise  13 × 2 hrs. compulsory                  
Course curriculum:
    Lecture 1. Inner and outer dynamic system description in continuous and discrete domain.
2. State feedback control.
3. State controller design with disturbance compensation.
4. State controller design with state estimator.
5. State control design generalization, appropriate structures for state control design.
6. Case study of technical problem.
7. Fuzzy sets, linguistic variable.
8. Inference rules, fuzzification, defuzzification.
9. Rule systems, fuzzy controllers.
10. Rule base creation of fuzzy controller by empiric knowledge on system behavior.
11. Case study of technical problem.
12. Rule base creation of fuzzy controller by general metarules.
13. Case study of technical problem.
    Computer-assisted exercise 1. Basics of work with Matlab/Simulink/Control System Toolbox.
2. Dynamic properties of the system.
3. Case study: controller classic solution.
4. Case study: state controller I.
5. Case study: state controller II (with disturbance compensation).
6. Case study: state controller III (with state estimator).
7. Case study: state controller IV (with state estimator and disturbance compensation).
8. Basics of work with Matlab/Simulink/Fuzzy Logic Toolbox.
9. Case study: fuzzy controller I (intuitively).
10. Case study: fuzzy controller II (intuitively).
11. Case study: fuzzy controller III (by empiric knowledge).
12. Case study: fuzzy controller IV (by application metarules).
13. Accreditation test.
Literature - fundamental:
1. Hangos, K. M., Lakner, R., Gerzson, M.: Intelligent Control Systems (An Introduction with Examples), ISBN: 978-1-4757-7529-7,  Springer New York, NY
The study programmes with the given course:
Programme Study form Branch Spec. Final classification   Course-unit credits     Obligation     Level     Year     Semester  
CŽV full-time study CZV Bases of Mechanical Engineering -- GCr 5 Compulsory 1 1 W
B-MET-P full-time study --- no specialisation -- GCr 5 Compulsory 1 3 W