基于神经网络的非线性系统故障检测及容错控制方法

FAULT DETECTION AND FAULT TOLERANT CONTROL OF NONLINEAR SYSTEMS USING NEURAL NETWORKS

  • 摘要: 利用神经网络的非线性建模能力,提出了一种非线性系统的故障检测及容错控制方法.在本方法中,首先应用神经网络设计故障估计器,在线估计系统故障向量,实现故障检测;在此基础上,引入补偿控制器,消除故障对系统运行的影响,从而实现容错控制.同时基于Lyapunov方法进行了稳定性分析.

     

    Abstract: This paper proposes a fault detection and fault tolerant control method for a class of nonlinear systems based on neural networks. In the approach, a fault-estimator is designed using neural networks for on-line estimation of faults, then the fault detection is achieved. Once a fault is detected, a compensating controller is introduced into the post-fault systems to accommodate the faults. The stability analysis is also given based on Lyapunov method. Finally, the proposed method is used in fault detection and fault tolerant control of nonlinear DC-motor, simulation results demonstrate the effectiveness of the proposed method.

     

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