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

机译:基于半马尔可夫跳跃模型的基于无源性的混沌神经网络对执行器故障的容错同步控制

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摘要

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.
机译:本文讨论了带有执行器故障的神经网络基于被动性的容错同步问题。首次使用半马尔可夫跳跃模型将执行器故障建模为随机变量。提出了确保同步误差系统可靠地被动的准则。然后,设计了所需的容错控制器,该控制器考虑了可能的执行器故障。数值例子说明了我们提出的设计方法的有效性。

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