基于故障跟踪估计器的非线性时滞系统故障诊断

Fault diagnosis for nonlinear time-delay systems based on fault tracking approximator

提出一种可有效检测和估计一类非线性时滞系统故障的故障跟踪估计器.根据预测控制和迭代学习控制的思想,在所选取的优化时域长度内,通过迭代算法调节故障跟踪估计器中的可调参数,使之逼近系统中实际发生的故障.与以往基于观测器的故障诊断方法不同的是,故障跟踪估计器可同时检测和估计系统中发生的故障,而且针对不同类型的故障亦有很好的适应性.仿真结果表明了所提出算法的可行性和有效性.

A fault tracking approximator-based method is proposed for ;ault detection and identification for a class of nonlinear time-delay systems. Motivated by the predictive control and iterative learning control theory, an iterative learning algorithm is designed to update the adjustable parameter in the fault tracking approximator within a specified horizon. The adjustable parameter can give an estimation of the real fault occurred in the system. Different from the traditional fault observers based fault diagnosis methods, the approach proposed in this paper can not only detect the system faults, but also approximate the fault function, and can easily accommodate different kinds of faults. Finally, simulatiom results show the feasibility and effectiveness of the proposed approach.