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

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. ? 2021 Elsevier Ltd. All rights reserved.

Automated summary

In this paper, robust stabilization for FO delayed nonlinear uncertain system with disturbance is achieved using EID with internal model for the first time, and applied to FMNNs. A FO state-feedback controller is designed and gains are derived by LMI. Comparisons between EID approach with and without internal model, as well as observer-based method, are provided to emphasize the effectiveness of internal model control, with examples for FMNNs and a practical example showing the accuracy of the proposed results.