Optimization Design of Fuzzy Controller Based on Improved Ant Colony Algorithm

In this paper, a fuzzy controller is designed for nonlinear time delay system. Because of the selection of membership functions and fuzzy rules of the fuzzy controllers depends mainly on the experience of experts and the control effects are not good owing to the randomicity and subjectivity of the experience, a method of multi-colony evolvement ant colony algorithm based on idle ant colony system is proposed. This algorithm adopts multi-colony parallel optimize based on improved ACO algorithm, the ACO implementation including data initialization, solution construction and pheromone update are improved. It can optimize the membership functions and fuzzy rules synchronously. Simulation result shows that this algorithm is feasible and effective.