A hybrid genetic algorithm and bacterial foraging approach for global optimization
Information Sciences: an International Journal
A hybrid least square-fuzzy bacterial foraging strategy for harmonic estimation
IEEE Transactions on Evolutionary Computation
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Bio-inspired node localization in wireless sensor networks
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
An improved bacterial foraging optimization
ROBIO'09 Proceedings of the 2009 international conference on Robotics and biomimetics
Adaptive control of DC motor using bacterial foraging algorithm
Applied Soft Computing
ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part I
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Proportional integral derivative (PID) controller tuning is an area of interest for researchers in many disciplines of science and engineering. This paper presents a new algorithm for PID controller tuning based on a combination of the foraging behavior of E coli bacteria foraging and Particle Swarm Optimization (PSO). The E coli algorithm depends on random search directions which may lead to delay in reaching the global solution. The PSO algorithm may lead to possible entrapment in local minimum solutions. This paper proposed a new algorithm Bacteria Foraging oriented by PSO (BF-PSO). The new algorithm is proposed to combines both algorithms' advantages in order to get better optimization values. The proposed algorithm is applied to the problem of PID controller tuning and is compared with conveniently Bacterial Foraging algorithm and Particle swarm optimization.