Adaptive finite-time synchronization of fractional-order delayed fuzzy cellular neural networks

The adaptive finite-time synchronization problems are investigated for a class of fractional-order delayed fuzzy cellular neural networks (FODFCNNs). First, with the aid of the properties of the Mittag-Leffler function and the Laplace transform with the parameter, some novel fractional-order differential inequalities are established to provide new perspective to explore finite-time synchronization of fractional-order systems. Second, based on these inequalities and the designed adaptive controller, some novel sufficient conditions are given to guarantee the adaptive finite-time synchronization of FODFCNNs. Finally, the effectiveness of the results is demonstrated by a numerical example.(c) 2023 Elsevier B.V. All rights reserved.

Automated summary

This paper investigates the adaptive finite-time synchronization problems for a class of fractional-order delayed fuzzy cellular neural networks (FODFCNNs). First, new perspective is provided to explore finite-time synchronization of fractional-order systems by establishing novel fractional-order differential inequalities with the aid of the properties of the Mittag-Leffler function and the Laplace transform with the parameter. Second, sufficient conditions are given based on these inequalities and the designed adaptive controller to guarantee the adaptive finite-time synchronization of FODFCNNs. Finally, the effectiveness of the results is demonstrated by a numerical example.