An Effective Refinement Artificial Bee Colony Optimization Algorithm Based On Chaotic Search and Application for PID Control Tuning

Artificial Bee Colony algorithm is a global optimization algorithm which is motivated by the foraging behavior of honey bee swarms. Basic Artificial Bee Colony algorithm (ABC) has the advantages of strong robustness, fast convergence and high flexibility, fewer setting parameters, but it has the disadvantages premature convergence in the later search period and the accuracy of the optimal value which cannot meet the requirements sometimes. In this paper the Chaotic Local Search method is applied to solve the accuracy problem of global optimal value. The premature convergence issue of the Artificial Bee Colony algorithm has been improved by increasing the number of scout and rational using of the global optimal value and Chaotic Search. The application of the Chaotic Search ABC (CABC) algorithm in the PID Control parameters tuning is also simulated in this paper.