in this paper we consider the problem of delay-dependent robusth1 control for uncertain fuzzy systems with time-varying delay. the takagi–sugeno (t–s) fuzzy model is used to describe such systems. time-delay isassumed to have lower and upper bounds. based on the lyapunov-krasovskiifunctional method, a sufficient condition for the existence of a robust $h_{infty}$controller is obtained. the fuzz...

Fuzzy-model-based (FMB) control approach provides a systematic and effective way to control nonlinear systems. It has been shown by various applications (Lam et al., 1998; Lian et al., 2006; (b)Tanaka et al., 1998) that FMB control approach performs superior to some traditional control approaches. Based on the T-S fuzzy model (Sugeno & Kang, 1988; Takagi & Sugeno, 1985) the system dynamics of t...

A technique for the modeling of nonlinear control processes using fuzzy modeling approach based on the Takagi–Sugeno fuzzy model with a combination of genetic algorithm and recursive least square is proposed. This paper discusses the identification of the parameters at the antecedent and consequent parts of the fuzzy model. For the antecedent fuzzy parameters, genetic algorithm is used to tune ...

Takagi-Sugeno (TS) fuzzy modeling and control techniques are applied to the classical nonlinear Ball and Beam problem. The nonlinear model is segmented to different local linear models. Local controllers are hence designed using LMI theory for achieving a robust control behavior for ball position. TS fuzzy modeling is applied to generate suitable fuzzy models, and the associated controllers. Us...

In this paper, we introduce a robust state feedback controller design using Linear Matrix Inequalities (LMIs) and guaranteed cost approach for Takagi-Sugeno fuzzy systems. The purpose on this work is to establish a systematic method to design controllers for a class of uncertain linear and non linear systems. Our approach utilizes a certain type of fuzzy systems that are based on Takagi-Sugeno ...

In this paper, we introduce a robust state feedback controller design using Linear Matrix Inequalities (LMIs) and guaranteed cost approach for Takagi-Sugeno fuzzy systems. The purpose on this work is to establish a systematic method to design controllers for a class of uncertain linear and non linear systems. Our approach utilizes a certain type of fuzzy systems that are based on Takagi-Sugeno ...

In this paper, we introduce a Takagi-Sugeno (TS) fuzzy model which is derived from a typical Multi-Layer Perceptron Neural Network (MLP NN). At first, it is shown that the considered MLP NN can be interpreted as a variety of TS fuzzy model. It is discussed that the utilized Membership Function (MF) in such TS fuzzy model, despite its flexible structure, has some major restrictions. After modify...

chaotic systems are nonlinear dynamic systems, the main feature of which is high sensitivity to initial conditions. to initiate a design process in fuzzy model, chaotic systems must first be represented by t-s fuzzy models. in this paper, a new fuzzy modeling method based on sector nonlinearity approach has been recommended for chaotic systems relating to initial condition variations using the ...

We establish the functional equivalence of a generalized class of Gaussian radial basis function (RBFs) networks and the full Takagi-Sugeno model (1983) of fuzzy inference. This generalizes an existing result which applies to the standard Gaussian RBF network and a restricted form of the Takagi-Sugeno fuzzy system. The more general framework allows the removal of some of the restrictive conditi...