GPFIS-Control: A fuzzy Genetic model for Control tasks

Author

Koshiyama, Adriano S. ; Escovedo, Tatiana ; Vellasco, Marley M. B. R. ; Tanscheit, Ricardo

Author_Institution

Dept. of Electr. Eng., Pontifical Catholic Univ. of Rio de Janeiro, Rio de Janeiro, Brazil

fYear

2014

fDate

6-11 July 2014

Firstpage

1953

Lastpage

1959

Abstract

This work presents a Genetic Fuzzy Controller (GFC), called Genetic Programming Fuzzy Inference System for Control tasks (GPFIS-Control). It is based on Multi-Gene Genetic Programming, a variant of canonical Genetic Programming. The main characteristics and concepts of this approach are described, as well as its distinctions from other GFCs. Two benchmarks application of GPFIS-Control are considered: the Cart-Centering Problem and the Inverted Pendulum. In both cases results demonstrate the superiority and potentialities of GPFIS-Control in relation to other GFCs found in the literature.

Keywords

fuzzy control; fuzzy reasoning; genetic algorithms; nonlinear control systems; GPFIS-control; canonical genetic programming; cart-centering problem; fuzzy genetic model; genetic fuzzy controller; genetic programming fuzzy inference system for control tasks; inverted pendulum; multigene genetic programming; Equations; Fuzzy sets; Genetic algorithms; Genetic programming; Mathematical model; Pragmatics; Fuzzy Logic Control; Genetic Fuzzy Controller; Muti-Gene Genetic Programming;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4799-2073-0

Type

conf

DOI

10.1109/FUZZ-IEEE.2014.6891733

Filename

6891733