一类基于神经网络非线性观测器的鲁棒故障检测和诊断

Robust fault detection and diagnosis based on neural network nonlinear observer

利用神经网络的非线性建模能力 ,对一类具有建模不确定项的非线性系统提出一种基于观测器的故障检测和诊断的方法。设计的观测器不仅能实现故障检测 ,而且应用神经网络设计的故障估计器能在线估计系统中的故障向量。通过分析验证了该方法对系统中的建模误差和外部扰动具有良好的鲁棒性。

A robust fault detection and diagnosis strategy based on observer for nonlinear systems with unknown uncertainty is presented. A neural network is constructed to approximate the fault on-line. The nonlinear observer can not only detect fault, but also realize the fault diagnosis. It is proved that the scheme has good robustness against modeling error and uncertainty. At last, simulations of a three-tank system illustrate the effectiveness of the proposed methodology.