Ant algorithms for discrete optimization
Artificial Life
Ant colony optimization theory: a survey
Theoretical Computer Science
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
Applied Computational Intelligence and Soft Computing
RFID networks planning using BF-PSO
ICIC'12 Proceedings of the 8th international conference on Intelligent Computing Theories and Applications
Controller parameter optimization for nonlinear systems using enhanced bacteria foraging algorithm
Applied Computational Intelligence and Soft Computing
Hi-index | 0.00 |
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.