基于迭代学习控制的一类分布参数系统故障诊断

摘要

This paper investigated the problem of Fault diagnosis for a class of parabolic linear distributed parameter system based on iterative learning control. A fault estimator is proposed for the actual systems,and an iterative learning fault approximated algorithm is established using residual signal. The algorithm can guaranteed the convergence of fault error and residual signal with iterative number. The sufficient conditions for algorithm convergence and detail proof are given. Finally ,a numerical examples verify the validity of the algorithm.%利用迭代学习控制方法，研究了一类线性抛物型分布参数系统的故障诊断问题。首先设计了与实际系统对应的故障跟踪估计器，并利用残差信号构建基于迭代学习的故障逼近算法，该算法可同时保证故障偏差和残差信号沿迭代轴收敛。其次，给出了该学习控制算法一致收敛的充分条件，并详细证明了算法的收敛性。最后，利用数值例子验证了所给算法的有效性。