Passivity-based fault-tolerant synchronization control of chaotic neural networks against actuator faults using the semi-Markov jump model approach

The problem of passivity-based fault-tolerant synchronization for neural networks with actuator failures is addressed in this paper. The actuator failures are modeled as random variables by using the semi-Markov jump model for the first time. A criterion is proposed to ensure that the synchronization error system is reliably passive. Then, a desired fault-tolerant controller is designed, which takes the possible actuator failures into account. A numerical example is given to show effectiveness of our proposed design method.