Title :
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
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;
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
DOI :
10.1109/MED.2009.5164507
