Tuning fuzzy PID controllers using ant colony optimization

Author

Boubertakh, Hamid ; Tadjine, Mohamed ; Glorennec, Pierre-Yves ; Labiod, Salim

Author_Institution

LAMEL, Univ. of Jijel, Jijel, Algeria

fYear

2009

fDate

24-26 June 2009

Firstpage

13

Lastpage

18

Abstract

Ant colony optimization (ACO) is one of the swarm intelligence (SI) techniques. It is a bio-inspired optimization method that has proven its success through various combinatorial optimization problems. This paper proposes an ant colony optimization algorithm for tuning fuzzy PID controllers. First, the design of typical Takagi-Sugeno (TS) fuzzy PID controllers is investigated. The tuning parameters of these controllers have physical meaning which makes its tuning task easier than conventional PID controllers. Simulation examples are provided to illustrate the efficiency of the proposed method.

Keywords

control system synthesis; fuzzy control; optimisation; three-term control; Takagi-Sugeno fuzzy system design; ant colony optimization; combinatorial optimization problem; fuzzy PID controller tuning; swarm intelligence technique; Ant colony optimization; Automatic control; Control systems; Error correction; Fuzzy control; Fuzzy systems; Industrial control; Optimization methods; Takagi-Sugeno model; Three-term control; Ant colony optimization; Fuzzy PID controllers; Takagi-Sugeno fuzzy systems; classical PID controllers;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation, 2009. MED '09. 17th Mediterranean Conference on

Conference_Location

Thessaloniki

Print_ISBN

978-1-4244-4684-1

Electronic_ISBN

978-1-4244-4685-8

Type

conf

DOI

10.1109/MED.2009.5164507

Filename

5164507