This paper presents the stability conditions of the Takagi-Sugeno (T-S) fuzzy sampled-data filter. The error system between the T-S fuzzy system and fuzzy filter is presented. In the sense of the Lyapunov stability analysis, the stability conditions are given, which can be represented in terms of linear matrix inequalities (LMIs). The proposed stability conditions utilize the different approach...

Fuzzy set theory and fuzzy logic are the convenient tools for handling uncertain, imprecise, or unmodeled data in intelligent decision-making systems. The utility of fuzzy logic in system controls domain is presented in the context of a mobile robot navigation control application. The Takagi-Sugeno controller is a fuzzy model capable of approximating a wide class of nonlinear systems by decompo...

This paper presents an active fault tolerant control (FTC) strategy for induction motor drive that ensures trajectory tracking and offset the effect of the sensor faults despite the presence of load torque disturbance. The proposed approaches use a fuzzy descriptor observer to estimate simultaneously the system state and the sensor fault. The physical model of induction motor is approximated by...

This paper presents a survey on the ex isting methods for the stability analysis of fuzzy control systems including both conventional Mamdani s rule based fuzzy controllers and Takagi Sugeno controllers The overview considers several approaches including input output stability frequency response methods Lyapunov techniques and qualitative methods The paper also sumarizes the new stability techn...

Takagi–Sugeno (T–S) fuzzy models play an important role in nonlinear control because they can be used to approximate nonlinear systems. Also, for the affine T–S fuzzy models, the local linear sub-system properties can be easily related to the physics of the controlled nonlinear system. This is one advantage of the affine T–S fuzzy models relative to the homogeneous T–S fuzzy models. In the lite...

In this work, three topics which are important for the further development of fuzzy systems are chosen to be investigated. First, the mathematical aspects of fuzzy relational equations (FREs) are explored. Solving FREs is one of the most important problems in fuzzy systems. In order to identify the algebraic information of the fuzzy space, two new tools, called fuzzy multiplicative inversion an...

In this study, we propose a novel method for modeling dynamic hysteresis. Hysteresis is a widespread phenomenon that is observed in many physical systems. Many different models have been developed for representing a hysteretic system. Among them, the Duhem model is a classical nonlinear dynamic hysteresis model satisfying the properties of hysteresis. The purpose of this work is to develop a no...

This paper presents a sum of squares (SOS) approach to guaranteed cost control of polynomial discrete fuzzy systems. First, we present a polynomial discrete fuzzy model that is more general representation of the well-known discrete Takagi-Sugeno (T-S) fuzzy model. Secondly, we derive a design condition based on polynomial Lyapunov functions that contain quadratic Lyapunov functions as a special...

Fuzzy set theory and fuzzy logic are the convenient tools for handling uncertain, imprecise, or unmodeled data in intelligent decision-making systems. The utility of fuzzy logic in system controls domain is presented in the context of a mobile robot navigation control application. The Takagi-Sugeno controller is a fuzzy model capable of approximating a wide class of nonlinear systems by decompo...

In recent years, there has been significant interest in the study of stability analysis and con‐ troller synthesis for Takagi-Sugeno(T-S) fuzzy systems, which has been used to approximate certain complex nonlinear systems [1]. Hence it is important to study their stability analysis and controller synthesis. A rich body of literature has appeared on the stability analysis and synthesis problems ...