Essentials of fuzzy modeling and control
Essentials of fuzzy modeling and control
Fuzzy Control and Modeling: Analytical Foundations and Applications
Fuzzy Control and Modeling: Analytical Foundations and Applications
Control Systems Engineering
Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic
Information Sciences: an International Journal
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Interval type-2 fuzzy logic control systems (IT2 FLCSs) have the potential of handling uncertainties better than type-1 FLCSs. However, lack of systematic design methodology of IT2 FLCSs limits their utility. This paper presents systematic methods to design interval IT2 Takagi-Sugeno-Kang (TSK) FLCSs that are PD-type and PI-type fuzzy controllers to satisfy certain desired transient response. We adopt the MacVicar-Whelan rule-base system and present general schemes for the design of IT2 TSK FLCSs, that include the design of the TSK consequent parameters. To validate the performance of the proposed controllers, some nonlinear plants have been considered. Results show that the IT2 TSK FLCSs satisfy the desired performance measures in terms of a set point tracking. Moreover, they reveal remarkable improvements in comparison to their type-1 counterparts for the plants considered in this paper.