Exponential Stability of Fractional-Order Fuzzy Multilayer Networks With Short Memory and Noninstantaneous Impulses via Intermittent Control
Yao Xu, Zui Chen, Wenxue Li, Yongbao Wu
Abstract
Many practical processes in the actual world may suffer from nonnegligible instantaneous state resets and then persist for a set amount of time, which can be characterized by noninstantaneous impulses. In this article, intermittently controlled fractional-order fuzzy multilayer complex networks with short memory and noninstantaneous impulses are considered, which give rise to a new, hybrid dynamical system that offers a wide range of applications. By employing a discontinuously intermittent control scheme, the exponential stability issue of the above-mentioned networks is studied and supported by the Lyapunov method and graph theory. In the analysis of exponential stability, stabilized and destabilized noninstantaneous impulsive effects are discussed respectively. Ultimately, main results are applied in the typical model of fractional-order competitive neural networks, and illustrative numerical simulations are conducted to show the effectiveness of theoretical analysis.