Adaptive Synchronization for a Class of Uncertain Fractional-Order Neural Networks

Entropy

Heng Liu³  Shenggang Li³  Hongxing Wang¹  Yuhong Huo¹  Junhai Luo²  J. A. Tenreiro Machado⁴ 

[1] Department of Applied Mathematics, Huainan Normal University, Huainan 232038, China; E-Mails:;School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China; E-Mail:;College of Mathematics and Information Science, Shaanxi Normal University, Xi’an 710119, China; E-Mail:;College of Mathematics and Information Science, Shaanxi Normal University, Xi’an 710119, China; E-Mail

关键词: fractional-order neural network;    adaptive control;    synchronization;   

DOI  :  10.3390/e17107185

来源: mdpi

【 摘 要 】

In this paper, synchronization for a class of uncertain fractional-order neural networks subject to external disturbances and disturbed system parameters is studied. Based on the fractional-order extension of the Lyapunov stability criterion, an adaptive synchronization controller is designed, and fractional-order adaptation law is proposed to update the controller parameter online. The proposed controller can guarantee that the synchronization errors between two uncertain fractional-order neural networks converge to zero asymptotically. By using some proposed lemmas, the quadratic Lyapunov functions are employed in the stability analysis. Finally, numerical simulations are presented to confirm the effectiveness of the proposed method.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.