Based on a Takagi–Sugeno (T–S) fuzzy model and an inverse system method, this paper deals with the problem of actuator fault estimation for a class of nonlinear dynamic systems. Two different estimation strategies are developed. Firstly, T–S fuzzy models are used to describe nonlinear dynamic systems with an actuator fault. Then, a robust sliding mode observer is designed based on a T–S fuzzy m...

In this paper, the nonlinear systems with time-varying delays and parametric uncertainties are represented by an equivalent Takagi-Sugeno type fuzzy model. Based on Convex combination property, Lyapunov criterion, and Razumikhin theorem, some sufficient conditions are derived under which the parallel-distributed fuzzy control can stabilize the whole uncertain fuzzy time-delay systems asymptotic...

This paper, deals with an indirect adaptive fuzzy control of discrete-time MIMO nonlinear systems with parametric variations. The synthesis of the state feedback control law is based on the T-S fuzzy models developed by a local description of the considered system. In the first step, gradient method is used to adjust model parameters locally estimated by the fuzzy model. The state feedback cont...

This paper is concerned with the stability analysis for T-S fuzzy control systems. By exploiting the property of the structure of fuzzy inference engine, an equivalence relation on index set of the product of fuzzy rule weights is defined. Further, a new stability criterion is proposed by using the equivalence relation, and formulated into progressively less conservative sets of linear matrix i...

In this paper, we consider the fuzzy model-based designs for the complete synchronization of chaotic systems. T-S fuzzy model for chaotic systems are exactly derived. Based on the T-S fuzzy model, the fuzzy logic controllers for chaotic synchronization are designed via Linear Matrix Inequality (LMI). Lyapunov Exponent of lorenz system is calculated, one of them is positive which represents the ...

This paper deals with the stabilization design problem for a class of continuous-time Takagi-Sugeno (T-S) fuzzy model-based control systems. A stabilization design based on fuzzy Lyapunov function and a non-parallel distributed compensation (non-PDC) control law has been proposed. Sufficient stabilization conditions are derived. The conditions for the solvability of the state feedback controlle...

The relevance of bifurcation analysis in Takagi–Sugeno (T–S) fuzzy systems is emphasized mainly through examples. It is demonstrated that even the most simple cases can show a great variety of behaviors. To understand the richness of asymptotic dynamics, one can find in T–S systems, a methodology is proposed by invoking bifurcation theory. Several local and global bifurcations (some of them, de...

Aneural-learning fuzzy technique is proposed for T–S fuzzy-model identification ofmodel-free physical systems. Further, an algorithm with a defined modelling index is proposed to integrate and to guarantee that the proposed neural-based optimal fuzzy controller can stabilize physical systems; the modelling index is defined to denote the modelling-error evolution, and to ensure that the training...

Stability is of primary importance for any control systems. Stability of both linear and nonlinear uncertain systems has received a considerable attention in the past decades (see for example, Tanaka & Sugeno, 1992; Tanaka, Ikeda, & Wang, 1996; Feng, Cao, Kees, et al. 1997; Teixeira & Zak, 1999; Lee, Park, & Chen, 2001; Park, Kim, & Park, 2001; Chen, Liu, & Tong, 2006; Lam & Leung, 2007, and re...

it is firstly proved that the multi-input-single-output (miso) fuzzy systems based on interval-valued $r$- and $s$-implications can approximate any continuous function defined on a compact set to arbitrary accuracy.  a formula to compute the lower upper bounds on the number  of interval-valued fuzzy sets needed to achieve a pre-specified approximation  accuracy for an arbitrary multivariate con...