Automatedgeneration of fuzzy control system using genetic algorithm, 1995
Muforo, Remigius I.
1990-1999
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.
text
application/pdf
1995-05-01
thesis
Master of Science (MS)
Clark Atlanta University
Department of Computer and Information Science
Roy George
Georgia--Atlanta
http://hdl.handle.net/20.500.12322/cau.td:1995_muforo_remigius_i
