Fixed-/Preassigned-time stabilization of delayed memristive neural networks

This paper deals with the fixed-time stabilization (FXTS) and preassigned-time stabilization (PATS) problems for delayed memristive neural networks (DMNNs) via a unified controller. Firstly, we design a delayed controller to realize the FXTS of DMNNs. Moreover, the sufficient conditions and accurate time estimation of FXTS are presented. It is proved that the system states can achieve stabilization within a fixed time without being affected by the initial states. Then, by modifying the parameters of the same controller, DMMNs achieve stabilization within an arbitrary preassigned time, which gets rid of the limitation of system and controller parameters. Finally, the feasibility and validity of the main results are verified by numerical simulations. (c) 2022 Elsevier Inc. All rights reserved.

Automated summary

This paper addresses the fixed-time stabilization and preassigned-time stabilization problems for delayed memristive neural networks using a unified controller. It proposes a delayed controller for achieving fixed-time stabilization and presents sufficient conditions and accurate time estimation. It also introduces a parameter modification approach for achieving stabilization within an arbitrary preassigned time, removing the constraints on system and controller parameters.