基于有理平方根逼近的非高斯随机分布系统的故障诊断和容错控制

Fault diagnosis and tolerant control for non-Gaussian stochastic distribution control systems based on the rational square-root approximation model

随机分布系统指的是输入为常规向量而输出为系统输出的概率密度函数所描述的一类随机系统．该类系统控制算法的目标是选择一个控制输入使得系统的实际输出概率密度函数尽可能跟踪一个事先给定的概率密度函数．本文对采用有理平方根B样条逼近其输出概率密度函数的非高斯动态随机分布系统,提出了一种基于非线性自适应观测器的故障诊断方法．该方法可快速有效地诊断出非高斯随机分布系统故障．通过对故障系统的重组,使故障后系统的输出概率密度函数仍能跟踪给定的分布,实现了该随机系统的容错控制,提高了随机系统的可靠性．

Stochastic distribution control （SDC） systems are a group of systems where the outputs considered are the measured probability density functions （PDFs） of the system output whilst subjected to a normal crisp input. The purpose of the control algorithm design of such systems is to choose a control input such that the output PDF of the system output can follow a pre-specified PDF as close as possible. Using the rational square-root B-spline model to represent the dynamics between the output PDF and the input,a nonlinear adaptive observer based fault diagnosis algorithm is proposed to diagnose the fault in the dynamic part of the system in this paper. Through the controller reconfiguration,a good output PDF tracking can still be realized when fault occurs,which has been shown to be able to enhance the reliability of the SDC system.