Design of Interval Type-2 Fuzzy Logic Controllers

Abstract

Uncertainty is an inherent part of intelligent systems used in real-world applications [42]. The use of new methods for handling incomplete information is of fundamental importance [13]. Type-1 fuzzy sets used in conventional fuzzy systems cannot fully handle the uncertainties present in intelligent systems. Type-2 fuzzy sets that are used in type-2 fuzzy systems can handle such uncertainties in a better way because they provide us with more parameters [42]. This chapter deals with the design of intelligent systems using interval type-2 fuzzy logic for minimizing the effects of uncertainty produced by the instrumentation elements, environmental noise, etc. Experimental results include simulations of feedback control systems for non-linear plants using type-1 and type-2 fuzzy logic controllers; a comparative analysis of the systems’ response is performed, with and without the presence of uncertainty [68, 69].KeywordsMembership FunctionFuzzy Logic ControllerFuzzy Logic SystemPrimary MembershipSumming JunctionThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.