Stochastic reliable synchronization for coupled Markovian reaction–diffusion neural networks with actuator failures and generalized switching policies

• Published in: Applied mathematics and computation Vol. 357; pp. 88 - 106
• Main Authors: Zeng, Deqiang, Pu, Zhilin, Zhang, Ruimei, Zhong, Shouming, Liu, Yajuan, Wu, Guo-Cheng
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 15.09.2019
• Subjects: Actuator failures; Coupled Markovian reaction–diffusion neural networks (RDNNs); Generalized switching policies (GSPs); Mode-dependent reliable control; Synchronization; Generalized switching policies (GSPs); Synchronization; Mode-dependent reliable control; Actuator failures; Coupled Markovian reaction–diffusion neural networks (RDNNs)
• ISSN: 0096-3003; 1873-5649
• DOI: 10.1016/j.amc.2019.03.055

This paper is concerned with the synchronization of coupled Markovian reaction–diffusion neural networks (RDNNs) with actuator failures and generalized switching policies (GSPs) via mode-dependent reliable control. Different from some existing results with all known transition rates, GSPs are considered for coupled Markovian RDNNs, where each transition rate can be completely unknown or only its estimation is known, or each transition rate of some modes is completely unknown. To reflect more realistic behaviors, actuator failures are considered for coupled Markovian RDNNs, and a mode-dependent reliable control scheme is proposed. Then, a new Lyapunov–Krasovskii functional (LKF) is introduced, which fully utilizes the information on the slope of neuron activation functions. Based on the LKF, a synchronization criterion is established in the form of linear matrix inequalities (LMIs). Moreover, the mode-dependent reliable control gains are obtained. Finally, a numerical example is given to verify the effectiveness of the proposed results.