Fuzzy control of impact machines using genetic algorithms

Author

Sasaki, Motofumi ; Uchida, Takanobu ; Sasaki, Tom ; Koizumi, Kazuto

Author_Institution

Dept. of Mech. & Intelligent Syst. Eng., Toyama Univ., Japan

fYear

1997

fDate

29-31 Jul 1997

Firstpage

977

Lastpage

982

Abstract

A control design method for impact machines is proposed using fuzzy inference and genetic algorithms. The proposed fuzzy PID controller with output constraints employs only position measurements with no use of velocity measurements, and has the characteristics of optimal selection of fuzzification and defuzzification scaling factors, automatic selection of fuzzy rules, acquisition of smooth control input, high-speed, high-accuracy and robustness with respect to plant perturbations. By computer simulation, it is demonstrated that the proposed method is effective

Keywords

control system synthesis; digital simulation; fuzzy control; fuzzy set theory; genetic algorithms; inference mechanisms; manufacturing processes; position measurement; three-term control; control design method; defuzzification scaling factors; fuzzification scaling factors; fuzzy PID controller; fuzzy inference; fuzzy rules; genetic algorithms; impact machines; output constraints; position measurements; robustness; Automatic control; Control design; Fuzzy control; Genetic algorithms; Optimal control; Position measurement; Robust control; Three-term control; Velocity control; Velocity measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE '97. Proceedings of the 36th SICE Annual Conference. International Session Papers

Conference_Location

Tokushima

Type

conf

DOI

10.1109/SICE.1997.624892

Filename

624892