Impulsive stabilization of fuzzy neural networks with time-varying delays

Abstract

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 Lyapunov function, inequality techniques and linear matrix inequality approach. Two numerical examples are provided to illustrate the efficiency of impulsive stabilization for TSFNNs by using fixed impulsive interval and variable impulsive intervals, respectively. Mathematics Subject Classification 93C10 · 93D15

Global $$O(t^{-\alpha })$$ O ( t - α ) stabilization of fractional-order memristive neural networks with time delays

“…The article provides a novel way to construct a Lyapunov function and a new method to deal with fractional-order inequalities, which may be applied to discuss other properties or analyze other more complex systems such as the fractional-order form of the model explored in the literatures Chandrasekar and Rakkiyappan ( 2016 ), Lou et al. ( 2013 ), Shang ( 2014 , 2015 , 2016 ), Wang et al. ( 2003 ), Yang and Tong ( 2016 ) and so on.…”

“… 2016 ), impulsive stabilization (Chandrasekar and Rakkiyappan 2016 ; Huang 2010 ; Lou et al. 2013 ). Despite these fruitful achievements, some stabilization approaches can hardly be widely applied in practical problems due to high gain.…”

Terminal Sliding Mode Control with Adaptive Feedback Control in a Class of Chaotic Systems

“…Its control is effective, but it can only control system states coupled in the sliding mode surface; readers are referred to [1][2][3][4][5][6][7] for more detailed information. As for impulse control [8][9][10][11][12][13][14][15][16], they add impulse effects to continuous differential equation and, by constructing comparison system, establish relationships between parameters of system and impulse. Their controllers are effective, but design processes of their controllers are too much complex.…”