Brownian Distribution Guided Bacterial Foraging Algorithm for Controller Design Problem

Bacterial Foraging Optimization (BFO) algorithm is widely adopted to solve a variety of engineering optimization tasks. In this paper, the Brownian Distribution (BD) strategy guided BFO algorithm is proposed. During the optimization exploration, BD monitors and controls the chemotaxis operation of the BFO algorithm inorder to enhance the search speed and optimization accuracy. In the proposed algorithm, after undergoing a chemotaxis step, each bacterium gets mutated by a BD operator. In the proposed work, this algorithm is employed to design the PID controller for an AVR system and unstable reactor models. The success of the proposed method has been confirmed through a comparative analysis with PSO, BFO, adaptive BFO and PSO + BFO based hybrid methods existing in the literature. The result shows that, for unstable reactor models, the BD guided BFO algorithm provides better optimization accuracy compared to other algorithms considered in this study.

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