EID-based robust stabilization for delayed fractional-order nonlinear uncertain system with application in memristive neural networks

Xueqi Yao and Shouming Zhong

Chaos, Solitons & Fractals, 2021, vol. 144, issue C

Abstract: In this paper, the robust stabilization for fractional-order (FO) delayed nonlinear uncertain system with disturbance is obtained for the first time by using equivalent-input-disturbance (EID) with internal model. And the EID method is applied to FO memristive neural networks (FMNNS) as an application. The fractional-order state-feedback controller is designed, and the gains of controller can be derived by LMI. Three simulations are given, the comparison between EID approach with and without internal model is showed and the observer-based method is compared to emphasize the effectivity of internal model control. And the example for FMNNs and a simple practical example are given to show the accuracy of the proposed results.

Keywords: Fractional-order system; Uncertain system; Robust stabilization; Equivalent-input-disturbance; Memristive neural networks (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:144:y:2021:i:c:s0960077921000588

DOI: 10.1016/j.chaos.2021.110705

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