EE453

FUZZY SYSTEMS

Objectives

  • To understand the importance of fuzziness in real world scenarios
  • To expose students to fuzzy methods of analysing problems that involves incomplete or vague criteria
  • To understand the standards and techniques deployed in the development os a fuzzy system

 

Outcomes

  • Gain technical knowhow in dealing with fuzzy data
  • Imply the fuzzy rules and techniques in modelling a better prototype
  • Application of fuzzy systems in solving engineering problems

 

Unit – I

Different faces of imprecision – inexactness – Ambiguity – Undecidability - Fuzziness and certainty - Fuzzy sets and crisp sets.

 

Unit – II

Intersection of Fuzzy sets - Union of Fuzzy sets - the complement of Fuzzy sets - Fuzzy reasoning.

 

Unit – III

Linguistic variables - Fuzzy propositions - Fuzzy compositional rules of inference- Methods of decompositions and defuzzification.

 

Unit – IV

Methodology of Fuzzy Design - Direct & Indirect methods with single and multiple experts

 

Unit – V

Applications - Fuzzy controllers - DC motor speed control - Neuro Fuzzy systems, Fuzzy Genetic Algorithms.

 

REFERENCE

  • Zimmermann, H. J., “Fuzzy set theory and its applications”, Allied publishers limited, Madras, 1966.
  • Klir, G. J., andFolger, T., “Fuzzy sets, uncertainty and information”, PHI, New Delhi, 1991.
  • Earlcox, “The Fuzzy Systems Handbook”, AP Professional Cambridge, MA02139, 1994.