Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm | Zendy

V. Rajinikanth | Zendy; K. Latha | Zendy

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Controller Parameter Optimization for Nonlinear Systems Using Enhanced Bacteria Foraging Algorithm

Author(s) -

V. Rajinikanth,

K. Latha

Publication year - 2012

Publication title -

applied computational intelligence and soft computing

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.371

H-Index - 10

eISSN - 1687-9732

pISSN - 1687-9724

DOI - 10.1155/2012/214264

Subject(s) - pid controller , setpoint , control theory (sociology) , computer science , nonlinear system , controller (irrigation) , algorithm , foraging , convergence (economics) , control engineering , artificial intelligence , control (management) , engineering , temperature control , ecology , agronomy , physics , quantum mechanics , economics , biology , economic growth

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

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