Impulsive Stabilization for a Class of Neural Networks with Both Time-Varying and Distributed Delays

Impulsive Stabilization for a Class of Neural Networks with Both Time-Varying and Distributed Delays

Impulsive stabilization of fuzzy neural networks with time-varying delays

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...

Robust stability of stochastic fuzzy impulsive recurrent neural networks with\ time-varying delays

In this paper, global robust stability of stochastic impulsive recurrent neural networks with time-varyingdelays which are represented by the Takagi-Sugeno (T-S) fuzzy models is considered. A novel Linear Matrix Inequality (LMI)-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of uncertain fuzzy stochastic impulsive recurrent neural...

μ-Stability of Impulsive Neural Networks with Unbounded Time-Varying Delays and Continuously Distributed Delays

This paper is concerned with the problem of μ-stability of impulsive neural systems with unbounded time-varying delays and continuously distributed delays. Some μ-stability criteria are derived by using the Lyapunov-Krasovskii functional method. Those criteria are expressed in the form of linear matrix inequalities LMIs , and they can easily be checked. A numerical example is provided to demons...

ADAPTIVE FUZZY TRACKING CONTROL FOR A CLASS OF NONLINEAR SYSTEMS WITH UNKNOWN DISTRIBUTED TIME-VARYING DELAYS AND UNKNOWN CONTROL DIRECTIONS

In this paper, an adaptive fuzzy control scheme is proposed for a class of perturbed strict-feedback nonlinear systems with unknown discrete and distributed time-varying delays, and the proposed design method does not require a priori knowledge of the signs of the control gains.Based on the backstepping technique, the adaptive fuzzy controller is constructed. The main contributions of the paper...