AIMS Mathematics (Mar 2024)

Event-triggered fixed/preassigned time stabilization of state-dependent switching neural networks with mixed time delays

  • Jiashu Gao ,
  • Jing Han,
  • Guodong Zhang

DOI
https://doi.org/10.3934/math.2024449
Journal volume & issue
Vol. 9, no. 4
pp. 9211 – 9231

Abstract

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This study employed an event-triggered control (ETC) strategy to investigate the problems of fixed-time stabilization (FTS) and preassigned-time stabilization (PTS) for state-dependent switching neural networks (SDSNNs) that involved mixed time delays. To enhance the network's generalization capability and accelerate convergence stabilization, a more intricate weight-switching mechanism was introduced, then to mitigate transmission energy consumption, this paper proposed a tailored event-triggering rule that triggered the ETC solely at predetermined time points. This rule ensured the stability of the system while effectively reducing energy consumption. Using the Lyapunov stability theory and various inequality techniques, this paper presented new results for FTS and PTS of SDSNNs. The validity of these findings was supported by conducting data simulations in two illustrative examples.

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