Fault tolerant synchronization for a class of complex interconnected neural networks with delay
Fault tolerant synchronization for a class of complex interconnected neural networks with delay
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DOI：
10.1002/acs.2399
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发表时间：
2014-10
影响因子：
3.1
通讯作者：
Zhanshan Wang;Tie-shan Li;Huaguang Zhang
中科院分区：
文献类型：
--
作者：
Zhanshan Wang;Tie-shan Li;Huaguang Zhang
研究了一类复杂互联神经网络在传感器故障下的容错同步问题。针对传感器故障可能导致网络性能下降甚至不稳定的问题，设计了容错控制律来保证复杂互联神经网络的受控同步。基于李雅普诺夫稳定性理论和自适应方案，基于线性矩阵不等式技术设计了三种容错控制律。一种是被动容错控制律，另外两种是自适应容错控制律。后两种方法利用耦合系数的自适应调整机制来保证网络在传感器故障情况下的同步。仿真结果验证了所提方法的有效性。版权所有© 2013约翰威利父子有限公司.
This paper is concerned with the fault tolerant synchronization problem for a class of complex interconnected neural networks against sensor faults. As sensor faults may lead to performance degradation or even instability of the whole network, fault tolerant control laws are designed to guarantee the controlled synchronization of the complex interconnected neural networks. On the basis of Lyapunov stability theory and adaptive schemes, three kinds of fault tolerant control laws are designed on the basis of linear matrix inequality technique. One is the passive fault tolerant control law, the other two are adaptive fault tolerant control laws. The latter two methods use the adaptive adjusting mechanism of the coupling coefficients to ensure the synchronization of the networks in the presence of sensor faults. Simulation results are given to verify the effectiveness of the proposed methods. Copyright © 2013 John Wiley & Sons, Ltd.