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Course Title: Fuzzy Systems
Full Marks: 45 + 30
Course No: C.Sc. 621
Pass Marks: 22.5 + 15
Nature of the Course: Theory + Lab
Credit Hrs: 3
Course Description:
This course.deals with introduction, fuzzy mapping, membership functions, fuzzy knowledge based system, fuzzy controller, nonlinear systems and adaptive fuzzy controller, and hybrid systems.
Course Objectives:
- Introduce the concept of fuzzy logic.
- Design using fuzzy system.
Unit 1: Introduction to fuzzy set theory: 7Hrs
1.1 Probabilistic reasoning,
1.2 Fuzzy sets,
1.3 mathematics of fuzzy set theory,
1.4 operations on fuzzy sets,
1.5 comparison of fuzzy and crisp set theory.
Unit 2: Fuzzy mapping: 7Hrs
2.1 one to one mapping,
2.2 max-min principle,
2.3 extension principle,
2.4 implication rules – mamdani implications.
Unit 3: Membership functions: 8Hrs
3.1 Universe of discourse,
3.2 mapping inside fuzzy domain,
3.3 fuzzy membership mapping methods,
3.4 application to real world problems.
Unit 4: Fuzzy knowledge based systems: 7Hrs
4.1 Fuzzification,
4.2 Fuzzy knowledge base, rule base,
4.3 Data base for fuzzy,
4.4 Inference rules,
4.5 defuzzyfication methods of defuzzification.
Unit 5: Fuzzy controller: 6Hrs
5.1 Control strategies,
5.2 general PID controller,
5.3 Implementation of fuzzy systems in control ,
5.4 Direct fuzzy controller,
5.5 PI and PID controller,
5.6 Indirect fuzzy controller – fuzzy in handling the inner loops of control systems.
Unit 6: Nonlinear systems and adaptive fuzzy controller:6Hrs
6.1 Nonlinear systems,
6.2 modification in fuzzy systems for nonlinear control,
6.3 Adaptive control,
6.4 Adaptive control using fuzzy,
6.5 fuzzy sliding mode controls.
Unit 7: Hybrid systems: 4Hrs
7.1 Neuro- fuzzy and fuzzy genetic systems,
7.2 Applications to scientific problems.
Laboratory:
The laboratory exercises should contain all the features mentioned above.
Reference books:
1.Neural Networks and Fuzzy Logics, Bart Kosko, Pearson Education, NewDelhi, 2011 2.Fuzzy logic to engineering applications –Timothy J. Ross.
3.Fuzzy control –Drianlcov.
4.Fuzzy modeling and control –Yager.
