Fuzzy controller improvement through imperialist colonial algorithm

This paper presents a new method to improve designed fuzzy logic controllers using a novel optimization algorithm called Imperialist Colonial Algorithm (ICA). This new method considers both membership functions and rules. We claim that in order to have a better optimization, symmetric limitation on both membership functions and rules (rule table) should be eliminated. Furthermore, fuzzy logic controller is optimized using imperialist colonial algorithm which is a novel evolutionary optimization method. This approach is applied for auto tuning fuzzy controllers.