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Two Differences Between Interval Type-2 and Type-1 Fuzzy Logic Controllers: Adaptiveness and Novelty

Chapter
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 301)

Abstract

Interval type-2 fuzzy logic controllers (IT2 FLCs) have been attracting great research interests recently. Many reported results have shown that IT2 FLCs are better able to handle uncertainties than their type-1 (T1) counterparts. A challenging question is: What are the fundamental differences between IT2 and T1 FLCs? Once the fundamental differences are clear, we can better understand the advantages of IT2 FLCs and hence better make use of them. This chapter explains two fundamental differences between IT2 and T1 FLCs: (1) Adaptiveness, meaning that the embedded T1 fuzzy sets used to compute the bounds of the type-reduced interval change as input changes; and, (2) Novelty, meaning that the upper and lower membership functions of the same IT2 fuzzy set may be used simultaneously in computing each bound of the type-reduced interval. T1 FLCs do not have these properties; thus, a T1 FLC cannot implement the complex control surface of an IT2 FLC given the same rulebase.

Keywords

Fundamental differences Type-1 fuzzy set Karnik-Mendel algorithms Novelty Fuzzy logic control Example of interval type-2 fuzzy logic controller Linguistic uncertainties Interval type-2 fuzzy logic controller Switch point KM type-reducer Control surface Adaptive PI control Interval type-2 fuzzy set Adaptiveness Type-1 fuzzy logic controller Type-reduction 

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Machine Learning Lab, GE Global ResearchNiskayunaUSA

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