In this paper, we propose new sets of criteria for exponential robust stability of Takagi-Sugeno (T-S) fuzzy Hopfield neural networks. The L2−L∞ approach is applied to obtain new sets of stability criteria, under which T-S fuzzy Hopfield neural networks reduce the effect of external input to a prescribed level. These sets of criteria are presented based on the matrix norm and linear matrix ineq...

This paper investigates the problem of passive delayed static output feedback control for a class of fuzzy systems. The system is described by a statespace Takagi–Sugeno (T-S) fuzzy model with additive delays and interval parameter uncertainties. The aim is to design a fuzzy delayed static output feedback controller which ensures the closed-loop system is passive for all admissible uncertaintie...

This paper presents the relaxed nonquadratic stabilization conditions of discrete-time Takagi–Sugeno (T–S) fuzzy systems. To do this, we propose a new fuzzy controller and Lyapunov function by generalizing the nonparallel distributed compensation (non-PDC) control law and nonquadratic Lyapunov function, respectively. By exploiting Pólya’s theorem and algebraic properties of a homogeneous polyno...

The problem of robust control for uncertain discrete-time Takagi and Sugeno (T-S) fuzzy networked control systems (NCSs) is investigated in this paper subject to state quantization. By taking into consideration network induced delays and packet dropouts, an improved model of network-based control is developed. A less conservative delay-dependent stability condition for the closed NCSs is derive...

In this pape, a class of nonlinear time-delay systems based on the Takagi-Sugeno (T-S)fuzzy model is defined. We investigate the delay-independent stability of this model. A model-based fuzzy stabilization design utilizing the concept of the so-called “parallel distributed compensation” (PDC) is employed. The main idea of the controller design is to derive each control rule to compensate each r...

This paper addresses the robust H∞ fuzzy control problem for nonlinear uncertain systems with state and input time delays through Takagi–Sugeno (T–S) fuzzy model approach. The delays are assumed to be interval time-varying delays, and no restriction is imposed on the derivative of time delay. Based on Lyapunov–Krasoviskii functional method, delay-dependent sufficient conditions for the existenc...

This paper deals with the problem of robust stabilization for uncertain discrete stochastic fuzzy systems with time-varying delays. The uncertainties are time-varying but norm-bounded. The purpose is to design a state feedback fuzzy controller such that the resulting closed-loop system is robustly stochastically stable. Based on Takagi-Sugeno (T-S) fuzzy model, a delay-dependent sucient conditi...

Abstract In this paper, a stability control approach of flexible joint robot (FJR) based T-S fuzzy model using fuzzy Lyapunov function is proposed. First, the Takagi and Sugeno (T-S) fuzzy model is employed to approximate the flexible joint robot, then a fuzzy controller is developed based on parallel distributed compensation principle (PDC). The non-quadratic stability conditions for the flexi...

Alternative LMI Conditions for Takagi-Sugeno Systems Via Fuzzy Lyapunov Function This paper deals with the stability analysis and control design for continuous Takagi-Sugeno fuzzy systems in a linear matrix inequality (LMI) framework. New LMI stability conditions are obtained by applying a relaxation strategy in a recently proposed fuzzy Lyapunov function. In these new LMI stability conditions,...

In this paper, in order to control uncertain chaotic system, an adaptive fuzzy control(AFC) scheme is developed for the multi-input/multi-output plants represented by the Takagi-Sugeno(T-S) fuzzy models. The proposed AFC scheme provides robust tracking of a desired signal for the T-S fuzzy systems with uncertain parameters. The developed control law and adaptive law guarantee the boundedness of...