Title
Synchronization Analysis of Fractional-Order Neural Networks With Adaptive Intermittent-Active Control
Abstract
This paper concentrates on the study of adaptive control for the synchronization of fractional-order neural networks. Instead of classical adaptive control updating method, an intermittent-active updating strategy is proposed to adaptively tune the control gain in a fractional-order fashion. Moreover, quantization is brought into the control design to take into account the restricted bandwidth in signal transmission. Note that the suggested controller is basic yet effective in terms of the fractional-order system. The main theorem is established with the method of reduction to absurdity as well as Lyapunov stability theorem. Finally, simulation calculation is conducted to validate the effectiveness of our proposed method.
Year
DOI
Venue
2022
10.1109/ACCESS.2022.3191801
IEEE ACCESS
Keywords
DocType
Volume
Synchronization, Adaptive control, Quantization (signal), Stability analysis, Trajectory, Lyapunov methods, Licenses, Fractional-order system, quantized control, intermittent-active control, synchronization
Journal
10
ISSN
Citations 
PageRank 
2169-3536
0
0.34
References 
Authors
0
7
Name
Order
Citations
PageRank
Xin Han100.68
Fengna Cheng200.68
Shan Tang300.68
Yuyan Zhang400.68
Yao Fu500.34
Weiguo Cheng600.34
Liang Xu700.34