Local search strategy biogeography-based optimization algorithm for self-tuning of PID parameters

As a new kind of evolutionary algorithm, the Biogeography-based optimization algorithm has a good utilizing ability. However, its exploration ability needs to be improved. This paper presents an improved Biogeography-based optimization algorithm for self-tuning of PID. The proposed method integrates local search strategy and selection operation of differencial evolution (DE) with migration operator in original BBO to improve the efficiency of migration and overcome the premature convergence in BBO algorithm. Simulation results on two different cases show that the proposed method can find the optimum parameter of PID controller more quickly than the other compared approaches.