Generalized approach for GA based learning of FLC design parameters

Author

Anzar, Masood ; Azeem, Mohammad Fazle ; Chauhan, Tanveer ; Yadav, Anil Kumar

Author_Institution

Meerut Inst. of Eng. & Technol., Meerut, India

fYear

2011

fDate

28-30 Jan. 2011

Firstpage

1

Lastpage

7

Abstract

This paper aims at the Genetic Algorithm (GA´s) based tuning of fuzzy logic controller (FLC). A two-step approach is proposed to tune a fuzzy logic controller using genetic algorithm. Moreover, it has been tried to develop a stepwise method to tune a fuzzy logic controller with GA in less number of generations. Special attention has been given to the learning of knowledge base which can be used for the elimination of premise variable or the whole rule from the rule base.

Keywords

control system synthesis; fuzzy control; genetic algorithms; knowledge based systems; learning (artificial intelligence); FLC design parameters; fuzzy logic controller; genetic algorithm; knowledge base learning; stepwise method; Biological cells; Fuzzy logic; Gallium; Genetic algorithms; Knowledge based systems; Process control; Tuning; Fuzzy Logic Controller (FLC); Genetic Algorithm (GA); Knowledge Base (KB); Membership Functions (MF´s); Rule Base (RB); Scaling Factors (SF); Universe of Discourse (UPD);

fLanguage

English

Publisher

ieee

Conference_Titel

Power Electronics (IICPE), 2010 India International Conference on

Conference_Location

New Delhi

Print_ISBN

978-1-4244-7883-5

Type

conf

DOI

10.1109/IICPE.2011.5728108

Filename

5728108