Immune clone selection algorithm for fuzzy logic controller design

Abstract

This paper provides an overview on immune clone selection algorithm for the automated design and optimization of fuzzy logic controller. A new optimization method for fuzzy logic controller design is proposed. The membership functions of input and output variables are defined by six parameters, which are adjusted to maximize the performance index of the controller by using immune clone selection algorithm. This method can shorten coding length, incarnate the characteristic of mutation and improve the capability of search and convergence of algorithm. Simulation experiment on water level controller is discussed by using above method. The simulation results show that the fuzzy logic controller based on immune clone selection algorithm avoids premature effectively and prove its feasibility.