一类基于状态估计的非线性系统的智能故障诊断

针对一类含有建模误差的非线性系统,研究了基于状态估计的智能故障诊断方法.首先提出一种状态估计器设计方法;然后在进行状态估计的同时用RBF神经网络来逼近系统所发生的故障.故障估计器的输入为系统的状态估计,所估计出的故障既可用作故障容错控制,也可用作报警.根据微分同胚,将含有建模误差的非线性系统变换为易于分析的规范形式,并在此基础上分析了故障诊断系统的稳定性和鲁棒性.仿真例子证明了该方法的有效性.

Intelligent nonlinear fault diagnosis based on state estimator

A fault diagnosis method based on state estimator for a class of nonlinear systems is proposed. The states of system and the faults in system are estimated simultaneously. The inputs of the fault approximator are the estimated states. And the outputs estimated from the fault model can be used for fault alarm or for fault tolerant control. A diffeomorphism is applied to transform the nonlinear system into a new coordinate system. The stability and robustness of the system are analysized in detail. A simulation example shows the effectiveness of the approach.