Type-2 Combined T-S Adaptive Fuzzy Control

Abstract

For a class of nonlinear systems with a nonlinear relationship between input and output, a fuzzy control method combining interval type-2 and T-S fuzzy controller is proposed based on type-2 fuzzy system theory. In order to ensure its stability, anti-interference ability, and minimum approximation error, this design combines direct, indirect, supervised, and compensation control types to construct the controller. In this way, the structure of the controller not only has the characteristics of the type-2 fuzzy set, which can reduce the uncertainty of rules, but also has a T-S fuzzy model with linear combination of input variables, which can improve the modeling accuracy and reduce the number of rules of the system. By using the Lyapunov synthesis method, the global stability and the convergence of the closed-loop system under the condition that all variables are uniformly bounded are analyzed, and the adaptive laws of the system parameters are given as well. Finally, the effectiveness and superiority of the proposed method are verified by simulation.

Fuzzy logic system for drug storage based on the internet of things: a survey

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“…Hao et al [22] 2020 -fuzzy control A novel design technique given by r was used to create the interval type-2 mixed t-s adaptive fuzzy controller…”

Filling Control of a Conical Tank Using a Compact Neuro‐Fuzzy Adaptive Control System

“…In [22] a type 2 fuzzy controller Takagi Sugeno (TS) for a non-linear system is proposed, which combines different types of supervised control as direct, indirect, and compensation to build the controller. Employing the synthesis method of Lyapunov the global stability and the close loop system convergence are analyzed with the condition that all the variables are evenly delimited, besides the adaptive laws of the system parameters are also given.…”

Real-Time Metaheuristic Algorithm for Dynamic Fuzzification, De-Fuzzification and Fuzzy Reasoning Processes

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