An optimal fuzzy logic controller tuned with artificial immune system

Abstract

In this paper, a method for the tuning the membership functions of a Mamdani type Fuzzy Logic Controller (FLC) using the Clonal Selection Algorithm(CSA) a model of the Artificial Immune System(AIS) paradigm is examined. FLC's are designed for two problems, firstly the linear cart centering problem and secondly the highly nonlinear inverted pendulum problem. The FLC tuned by AIS is compared with FLC tuned by GA. In order to check the robustness of the designed FLC's white noise was added to the system, further, the masses of the cart and the length and mass of the pendulum are changed. The FLC's were also tested in the presence of faulty rules. Finally, Kruskal-Wallis test was performed to compare the performance of the GA and AIS. An insight into the algorithms are also given by studying the effect of the important parameters of GA and AIS. © 2013 Springer.