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Aperiodic strict intermittent control for fixed-/preassigned-time synchronization of delayed memristive neural
Leimin Wang1, Jinpeng Yang1, Guanghui Jiang1
1School of Artificial Intelligence and Automation, China University of Geosciences, China, Wuhan, 430074, China; Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems, Wuhan, 430074, China; Engineering Research Center of Intelligent Technology for Geo-Exploration, Ministry of Education, Wuhan, 430074, China.
None:
This paper investigates the fixed-/preassigned-time synchronization control problem for delayed memristive neural networks (DMNNs) with external disturbance and discontinuous activation functions. Considering the inherent irregularity and aperiodicity in neural network scheduling, an aperiodic strict intermittent control strategy is adopted. Based on this framework, a class of aperiodic strict intermittent controllers is designed to achieve fixed-time synchronization (FxTS) for DMNNs. By appropriately tuning the controller parameters, a corresponding preassigned-time synchronization (PaTS) scheme is further constructed. Moreover, by fixing the control period and the active duration within each period, the proposed scheme reduces to periodic strict intermittent control and can be extended to MNNs with continuous activation functions. Furthermore, sufficient conditions are derived to guarantee both FxTS and PaTS, and explicit estimates of the settling time are provided. Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed approach.
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