Finite-time stabilization for semi-Markov reaction–diffusion memristive NNs: A boundary pinning control scheme

Abstract

This paper focuses on the finite-time stabilization issue of a kind of reaction–diffusion memristive neural networks (RDMNNs) with semi-Markov jumping parameters. The boundary control scheme is employed and combined with generalized pinning control strategy to stabilize the considered RDMNNs in finite time while saving communication resources and control costs. A positive constant ϱ is designed in our controller, such that the sharp chattering phenomena in previous similar controllers can be greatly reduced. Moreover, the corresponding finite-time stabilization criterion and related corollaries are obtained by using variable substitution and inequality methods flexibly. Last but not least, an illustrative example is carried out to validate effectiveness and superiority of the developed approach.