Bio-Inspired Optimization of Interval Type-2 Fuzzy Controller Design

Abstract

This chapter presents a general framework for designing interval type-2 fuzzy controllers based on bio-inspired optimization techniques. The problem of designing optimal type-2 fuzzy controllers for complex nonlinear plants under uncertain environments is of crucial importance in achieving good results for realworld applications. Traditional approaches have been using genetic algorithms or trial and error approaches; however, results tend to be not optimal or require very large design times. More recently, bio-inspired optimization techniques, like ant colony optimization or particle swarm intelligence, have also been applied on optimal design of fuzzy controllers. In this chapter, we show how bio-inspired optimization techniques can be used to obtain results that outperform traditional approaches in the design of optimal type-2 fuzzy controllers.