Title :
Fault accommodation for complete synchronization of complex neural networks
Author :
Zhanshan Wang ; Fufei Chu ; Hongjing Liang ; Huaguang Zhang
Author_Institution :
Sch. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
Abstract :
This paper is concerned with the adaptive fault tolerant synchronization problem for a class of complex interconnected neural networks against sensor failure and coupling failure. As sensor and coupling failure may lead to performance degradation or even instability of the whole network, adaptive approach is proposed to adjust unknown coupling factors for the deteriorated network compensations, as well as to estimate controller parameters to compensate the effects of failed coupling. Through Lyapunov functions and adaptive schemes, three kind of fault tolerant controllers are constructed to ensure the synchronization of the networks in the presence of the network deterioration. Simulation results are given to verify the effectiveness of the proposed method.
Keywords :
Lyapunov methods; complex networks; controllers; failure analysis; fault tolerance; interconnected systems; neural nets; parameter estimation; sensors; synchronisation; Lyapunov functions; adaptive fault tolerant synchronization problem; adaptive schemes; complex interconnected neural network synchronization; controller parameter estimation; coupling factors; coupling failure; deteriorated network compensations; fault accommodation; fault tolerant controllers; performance degradation; sensor failure; Adaptive systems; Complex networks; Couplings; Fault tolerance; Fault tolerant systems; Symmetric matrices; Synchronization;
Conference_Titel :
Adaptive Dynamic Programming And Reinforcement Learning (ADPRL), 2013 IEEE Symposium on
Conference_Location :
Singapore
DOI :
10.1109/ADPRL.2013.6615008