Fault tolerant synchronization for a class of complex interconnected neural networks with delay

Abstract

SUMMARYThis 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.