Design an Interval Type-2 Fuzzy Logic Controller Using a Modified Biogeography-Based Optimization

Abstract

In this paper we apply modified biogeography-based Optimization to design an interval type-2 fuzzy logic controller to improve the performance of the plant control system. Biogeography-based optimization is a novel evolutionary algorithm that is based on the mathematical models of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In the Biogeography-based optimization model, problem solutions are represented as islands, and the sharing of features between solutions is represented as immigration and emigration between the islands. A modified version of the Biogeography-based optimization is applied to design interval type-2 fuzzy logic controller to get the optimal parameters of the membership functions of the controller. We test the optimal interval type-2 fuzzy logic controller obtained by modified biogeography-based Optimization using benchmark plants and the performance is compared with a Particle swarm optimization-based controller. Also this paper deals with the design of intelligent systems using interval type-2 fuzzy logic for minimizing the effects of uncertainty produced by instrumentation elements, environmental noise, etc. We found that the optimized membership functions for the inputs of a type-2 system to improve the performance of the system for high uncertainty (noise) levels...