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Applied Computational Intelligence and Soft Computing
Volume 2012, Article ID 536326, 7 pages
Research Article

Tuning PID Controller Using Multiobjective Ant Colony Optimization

1Ensi Enim, Monastir, Rabat, Tunisia
2Ensi Enim, Tunisia
3National Cancer Institute, 92513 Boulogne Billan Court Cedex, France

Received 1 February 2011; Revised 6 October 2011; Accepted 11 October 2011

Academic Editor: F. Morabito

Copyright © 2012 Ibtissem Chiha et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper treats a tuning of PID controllers method using multiobjective ant colony optimization. The design objective was to apply the ant colony algorithm in the aim of tuning the optimum solution of the PID controllers (, , and ) by minimizing the multiobjective function. The potential of using multiobjective ant algorithms is to identify the Pareto optimal solution. The other methods are applied to make comparisons between a classic approach based on the “Ziegler-Nichols” method and a metaheuristic approach based on the genetic algorithms. Simulation results demonstrate that the new tuning method using multiobjective ant colony optimization has a better control system performance compared with the classic approach and the genetic algorithms.