Date of Award
Department of Computer and Information Science
Dr. Roy George
Fuzzy logic based controllers have emerged to be an inexpensive and simple solution for complex control problems. The main components of the fuzzy logic control are the rule base, the membership functions, and the inference engine. Membership functions are used to combine the antecedents and consequent (of the rules) to determine the output of the rules. Fuzzy controllers, however, suffer from significant drawbacks such as the formulation of the membership functions and tuning the rule base. In this thesis, a genetic algorithm is used to generate the fuzzy logic controller's rule base and to tune the membership functions. Temperature and pressure control in a boiler plant is used as a test bed application.
Muforo, Remigius I., "Automatedgeneration of fuzzy control system using genetic algorithm" (1995). ETD Collection for AUC Robert W. Woodruff Library. 3694.