Adaptive quasi-synchronization control of heterogeneous fractional-order coupled neural networks with reaction-diffusion

Wei Chen, Yongguang Yu, Xudong Hai and Guojian Ren

Applied Mathematics and Computation, 2022, vol. 427, issue C

Abstract: In this paper, the quasi-synchronization problem of heterogeneous fractional-order coupled neural networks (HFCNNs) is studied. In addition, we also take the spatial diffusion effect into consideration, and design an adaptive controller to attenuate the interference of heterogeneous terms. On the one hand, for quasi-synchronization, we propose a nonlinear distributed control law based on local information exchange between neighboring nodes, so that the synchronization error converges to a regulable bounded domain with a certain decay rate. On the other hand, leader-following quasi-synchronization, the reference trajectory is designed in advance and the corresponding distributed controller is developed to make the synchronization errors still tending to the bounded set. Finally, the simulation results show that the theoretical results are correct.

Keywords: Heterogeneous coupled neural networks; Fractional-order; Adaptive control; Reaction-diffusion; Quasi-synchronization (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:427:y:2022:i:c:s009630032200220x

DOI: 10.1016/j.amc.2022.127145

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