Dynamic-Memory Protocol-Based Synchronization for Semi-Markov Jump Reaction-Diffusion CDNs

Abstract

This study investigates the synchronization of reaction-diffusion complex dynamical networks (CDNs) based on semi-Markov switching topology and an event-triggered protocol. The investigated model is rendered more practical via the introduction of a semi-Markov process for stochastic jump CDNs. Based on the internal dynamic variable history information, a dynamic-memory event-triggered strategy is proposed, wherein the primary novelty lies in its prior transmitted packets to enhance the control performance. This further reduces data transmission based on the dynamic threshold parameters. The Bessel-Legendre inequality is adopted to reduce the conservatism of the obtained results. In addition, sufficient synchronization conditions are established to ensure the stochastic stability of the error system for two different models (partial differential equations- and ordinary differential equations-based models). Furthermore, two examples are provided to illustrate the effectiveness of the theoretical results.