In this paper, the model of stochastic fuzzy Hopfield neural networks with time-varying delays and impulses (ISFVDHNNs) is established as a modified Takagi-Sugeno (TS) fuzzy model in which the consequent parts are composed of a set of stochastic Hopfield neural networks with time-varying delays and impulses. Then, the global exponential stability in the mean square for ISFVDHNNs is studied by e...

This paper is concerned with stabilization for a class of Takagi-Sugeno fuzzy neural networks (TSFNNs) with time-varying delays. An impulsive control scheme is employed to stabilize a TSFNN. We firstly establish the model of TSFNNs by using fuzzy sets and fuzzy reasoning and propose the problem of impulsive stabilization for this model. Then, we present several stabilization conditions based on...

NeuroFAST is an on-line fuzzy modeling learning algorithm, featuring high function approximation accuracy and fast convergence. It is based on a first-order Takagi-Sugeno-Kang (TSK) model, where the consequence part of each fuzzy rule is a linear equation. Structure identification is performed by a fuzzy adaptive resonance theory (ART)-like mechanism, assisted by fuzzy rule splitting and adding...

In general, i t is not easy to design a decentralized controller for nonlinear interconnected systems. In this study, the stability of nonlinear interconnected systems is studied via fuzzy decentralized control method. First, the nonlinear interconnected systems are represented by an equivalent Takagi-Sugeno type fuzzy model. If the state variables are unavailable, a fuzzy observer-based state ...

This paper presents a Takagi-Sugeno fuzzy model-based controller which stabilizes the attitude of spacecraft with a partially-filled fuel tank. First, the nonlinear equations of motion of spacecraft containing a liquid fuel store is presented briefly. Then, the fuzzy modeling and the parallel distributed compensation control technique are applied. The proposed fuzzy controller is a nonlinear co...

This paper presents a fuzzy tracking control design based on H∞ performance for nonlinear systems. The Takagi-Sugeno fuzzy model is employed to approximate a nonlinear system. Based on the H∞ tracking performance, the nonlinear system output is controlled to track a reference signal, and at the same time the tracking performance is attenuated to a prescribed level. Linear matrix inequalities (L...

The paper offers evolving Takagi–Sugeno (T–S) fuzzy models for a nonlinear benchmark represented by the pendulum-crane system and focused on the dynamics of pendulum angular position behavior. The rule bases and parameters of T–S fuzzy models are continuously evolved by an online identification algorithm in terms of computing the potentials of new data points. Accepting the pendulum angle as mo...

This paper examines the inverse control problem of nonlinear systems with stable dynamics using a fuzzy modeling approach. Indeed, based on the ability of fuzzy systems to approximate any nonlinear mapping, the nonlinear system is represented by a Takagi-Sugeno (TS) fuzzy system, which is then inverted for designing a fuzzy controller. As an application of the proposed inverse control methodolo...

This paper deals with the extension of the positive invariance approach to Takagi-Sugeno fuzzy systems. The saturations on the control are taken into account during the design phase. This attempt is firstly applied to a class of fuzzy systems. Sufficient conditions of asymptotic stability are given ensuring in the same time that the global control is always admissible inside a common polyhedral...