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Applied Computational Intelligence and Soft Computing
Volume 2012 (2012), Article ID 214264, 12 pages
Research Article

Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm

1Department of Electronics and Instrumentation Engineering, St. Joseph’s College of Engineering, Chennai 600 119, India
2Department of Instrumentation Engineering, MIT Campus, Anna University, Chennai 600 044, India

Received 29 April 2012; Revised 23 July 2012; Accepted 16 August 2012

Academic Editor: Serafín Moral

Copyright © 2012 V. Rajinikanth and K. Latha. 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.


An enhanced bacteria foraging optimization (EBFO) algorithm-based Proportional + integral + derivative (PID) controller tuning is proposed for a class of nonlinear process models. The EBFO algorithm is a modified form of standard BFO algorithm. A multiobjective performance index is considered to guide the EBFO algorithm for discovering the best possible value of controller parameters. The efficiency of the proposed scheme has been validated through a comparative study with classical BFO, adaptive BFO, PSO, and GA based controller tuning methods proposed in the literature. The proposed algorithm is tested in real time on a nonlinear spherical tank system. The real-time results show that, EBFO tuned PID controller gives a smooth response for setpoint tracking performance.