Aperiodic Intermittent Control Based Predefined-Time Synchronization of Spatiotemporal Neural Networks
Ying Qiao, Aminamuhan Abudireman, Abudujelil Abudurahman · 2025
This paper addresses the issue of predefined-time (PDT) synchronization of spatiotemporal neural networks (NNs) by proposing a novel aperiodic intermittent control (AIC). First, a new lemma concerning PDT stability of general nonlinear systems in the intermittent sense is established. Second, a novel AIC is designed to mitigate the control burden and chattering phenomena associated with traditional sign function-based controllers. Third, by integrating Gauss theorem, the Lyapunov function method, the developed PDT stability lemma, and the proposed AIC, an in-depth exploration of the PDT synchronization problem of spatiotemporal NNs is conducted. Finally, the validity and feasibility of the theoretical findings are tested through numerical simulation experiments.