基于迭代学习的离散线性时变系统故障诊断

针对一类离散线性时变系统的故障诊断问题,提出一种新的故障检测与估计算法.该算法通过引入虚拟故障构建离散故障跟踪估计器,在选取的优化时域内,利用估计器输出和系统实际输出产生的残差信号,采用迭代学习算法来调节虚拟故障,使虚拟故障逼近系统中实际发生的故障,从而达到对系统故障诊断的目的.该方法不仅能检测出系统不同类型的故障,还可以实现对故障信号的精确估计.仿真结果验证了所提出方法的有效性.

Fault diagnosis of discrete linear time-varying system based on iterative learning

Aiming at the fault diagnosis in a class of discrete linear time-varying system, a novel fault detection and
estimation algorithm is proposed. This algorithm uses an introduced virtual fault to construct a discrete fault tracking
estimator, and then uses the iterative learning algorithm to regulate the virtue fault close to the practical fault based on the
difference between outputs of the estimator and the practical system within the chosen optimization time, thereby reaching
the end of the fault diagnosis. This algorithm not only can detect the different-type fault of the system, but also can estimate
the fault signal accurately. Simulation results show the effectiveness of this algorithm.