基于未知输入观测器的非线性广义系统执行器故障检测和重构

针对一类含有未知扰动广义非线性系统的执行器故障,本文提出一种重构算法。首先设计未知输入观测器对干扰鲁棒,作为故障检测观测器。检测到发生故障后,通过提出含有误差比例项和积分项的故障估计算法,形成自适应观测器,实现准确快速地估计故障,同时估计状态变量。根据李雅普诺夫稳定理论给出估计误差一致最终有界的充分条件。最后仿真验证该类观测器和重构算法的有效性。     

含未知输入观测器的广义系统故障诊断

基于未知输入观测器设计和故障诊断的概念,讨论含未知输入的Lipschitz条件下非线性广义系统传感器故障诊断问题。在非线性广义系统中,通过引入传感器的故障信号,重新构造非线性广义系统,设计基于未知输入观测器,在满足Lipschitz条件下,实现了传感器故障的检测与分离。给出数值仿真算例验证该算法的有效性。     

Unknown Input Fault Detection and Isolation Observer Design for Neutral Systems

This paper deals with actuator fault diagnosis of neutral delayed systems with multiple time delays using an unknown input observer. The main purpose is to design an observer that guarantees the asymptotic stability of the estimate error dynamics and the actuator fault detection. The existence conditions for such an observer are established. The main problem studied in this paper aims at designing observer‐based fault detection and isolation. The designed observer enhances the robust diagnosis performance, including rapidity and accuracy, and generates residuals that enjoy perfect decoupling properties among faults. Based on Lyapunov stability theory, the design of the observer is formulated in terms of linear matrix inequalities, and the diagnosis scheme is based on a bank of unknown input observers for residual generation that guarantees fault detection and isolation in the presence of external disturbances. A numerical example is presented to illustrate the efficiency of the proposed approach.     

一类具有未知参变量的非线性系统的鲁棒故障诊断

讨论了一类含有状态和输入未知参变量的非线性系统的故障诊断问题,在满足一些几何条件的情况下,该类系统可化成两类不同的子系统。对于其中一类不受故障影响的子系统,得到了其非线性自适应观测器及参数自适应律的设计;另一类受故障影响的子系统的状态是可测的,给出了该类子系统的基于模型监测和故障诊断的观测方案。然后,给出了用于验证本文所提方案的数字示例。     

Robust Unknown Input Observer Design for Linear Uncertain Time Delay Systems with Application to Fault Detection

In this paper, a novel approach is proposed to design a robust fault detection observer for uncertain linear time delay systems. The system is composed of both norm‐bounded uncertainties and exogenous signals (noise, disturbance, and fault) which are considered to be unknown. The main contribution of this paper is to present unknown input observer (UIO)‐based fault detection system which shows the maximum sensitivity to fault signals and the minimum sensitivity to other signals. Since the system contains uncertainty terms, an H_∞ model‐matching approach is used in design procedure. The reference residual signal generator system is designed so that the fault signal has maximum sensitivity while the exogenous signals have minimum sensitivity on the residual signal. Then, the fault detection system is designed by minimizing the estimation error between the reference residual signal and the UIO residual signal in the sense of H_∞ norm. A sufficient condition for the existence of such a filter is exploited in terms of certain linear matrix inequalities (LMIs). Application of the proposed method in a numerical example and an engineering process are simulated to demonstrate the effectiveness of the proposed algorithm. Simulation results show the validity of the proposed approach to detect the occurrence of faults in the presence of modeling errors, disturbances, and noise.     

非均匀采样数据系统的故障检测

针对目前涉及较少的非均匀采样数据系统故障检测研究,研究了一类基于观测器的故障检测滤波器设计问题;对于非均匀采样数据系统,首先利用提升技术推导出系统的提升状态空间模型,然后选用基于未知输入观测器的故障检测滤波器来作为残差产生器;同时给出一种故障检测滤波器设计的H_∞最优化设计方法,并给出其最优解及存在条件;最后通过一个示例进行验证,结果证明了该方法的有效性;该方法能够有效地实现对非均匀采样数据系统的故障的检测。     

基于未知输入集员滤波器的不确定系统故障诊断

针对一类具有参数不确定性和未知扰动的线性系统,提出了一种新的执行器故障诊断方法.将指定执行器故障视为未知输入,利用全对称多胞形近似状态边界,本文设计了一种未知输入全对称多胞形集员滤波器,以估计测量输出的上下边界.在此基础上,提出了一种利用一组未知输入滤波器的故障检测与分离策略.通过一个飞行控制系统的数值仿真验证了所提出方法的有效性.     

Adaptive Iterative Learning Control for a Class of Nonlinear Time-varying Systems with Unknown Delays and Input Dead-zone

This paper presents an adaptive iterative learning control (AILC) scheme for a class of nonlinear systems with unknown time-varying delays and unknown input dead-zone. A novel nonlinear form of dead-zone nonlinearity is presented. The assumption of identical initial condition for iterative learning control (ILC) is removed by introducing boundary layer function. The uncertainties with time-varying delays are compensated for by using appropriate Lyapunov-Krasovskii functional and Young0s inequality. Radial basis function neural networks are used to model the time-varying uncertainties. The hyperbolic tangent function is employed to avoid the problem of singularity. According to the property of hyperbolic tangent function, the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function (CEF) in two cases, while keeping all the closedloop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach.      

Tracking Control of Uncertain Nonlinear Systems With Unknown Constant Input Delay

A robust delay compensator has been developed for a class of uncertain nonlinear systems with an unknown constant input delay.The control law consists of feedback terms based on the integral of past control values and a novel filtered tracking error,capable of compensating for input delays.Suitable Lyapunov-Krasovskii functionals are used to prove global uniformly ultimately bounded(GUUB)tracking,provided certain sufficient gain conditions,dependent on the bound of the delay,are satisfied.Simulation results illustrate the performance and robustness of the controller for different values of input delay.     

一种基于最优未知输入观测器的故障诊断方法

针对含有未知输入干扰和噪音的不确定动态系统,使用全阶未知输入观测器(Unknown input observer, UIO)来消除干扰项,实现状态估计, 结合Kalman滤波器算法来求解状态反馈矩阵,以使得输出残差信号的协方差最小,从而增强系统对噪声的鲁棒性,实现了 一种基于最优未知输入观测器的残差产生器.采用极大似然比(Generalized likelihood ratio, GLR)的方法对残差信号进行评估,通过设定的阈值来提高诊断率. 最后以风力发电机组传动系统出现加性传感器故障和乘性传感器故障为例, 进行了残差信号的仿真,仿真结果说明了该方法的有效性.     

一种基于UIO观测器的故障检测方法

本文基于未知输入观测器，针对含有未知输入干扰的不确定动态系统，提出了一种故障检测的新方法。本文提出的方法与其它方法如特征向量配置法相比，具有条件要求较低，设计简单的优点。     

基于未知输入观测器的导弹间歇故障诊断

针对带有未知扰动和噪声的导弹间歇故障诊断问题,设计了一种基于未知输入观测器的导弹问题故障诊断方法,系统的输入部分或全部未知情况下也能获取系统状态的称为未知输入观测器.首先,为实现对外部扰动的解耦,设计降维未知输入观测器,并通过滑动时间窗口得到对间歇故障敏感而对未知扰动解耦的残差信号;然后,在满足误报率和漏报率的条件下,通过假设检验,确定了间歇故障发生时刻和消失时刻的可检测阈值;最后,对所提出的方法进行了仿真验证.仿真结果表明,在误差允许的范围内,设计的方法能够实现对间歇故障检测,满足实时性和准确性的要求.     

基于未知输入观测器的非线性时间序列故障预报

将未知非线性系统的输出作为时间序列并进行空间重构,针对得到的离散线性时变系统,提出了基于未知输入观测器的预测新方法.以实时拟合时间序列的线性AR模型作为时变系统的已知线性部分,将拟合误差作为时变系统的未知输入,实现了对非线性时间序列的一步预测.再利用递推预测的方法,将一步预测推广到N步预测,同时证明了该方法的预测误差有界.通过未知输入的预测值和状态的预测误差的变化可以方便地判断故障的发生,实现故障预报.仿真结果证明了方法的有效性.     

Fault Detection and Isolation Method Based on H−/H∞ Unknown Input Observer Design in Finite Frequency Domain

This paper proposes an actuator fault detection and isolation strategy based on a bank of unknown input observers with finite frequency specifications. In order to deal with actuator fault diagnosis problem, a bank of H _?/H _∞ unknown input observers are designed to generate residuals, which are insensitive to the corresponding faults but sensitive to the other actuators faults, and meanwhile robust against the unknown disturbances. In this paper, the actuator faults and unknown disturbances are considered to belong to finite frequency domains, and two finite frequency performance indices are used to measure the fault sensitivity and the disturbance robustness of the residuals. Furthermore, some parameters for extra design of freedom are introduced in the H _?/H _∞ unknown input observers design. Based on the generalised Kalman‐Yakubovich‐Popov (GKYP) lemma, the design conditions of the H _?/H _∞ unknown input observer are derived and formulated as linear matrix inequalities (LMIs). Finally, a VTOL aircraft model is used to demonstrate the performance of the proposed fault diagnosis scheme.     

一类非线性网络控制系统的故障检测

针对远程被控对象为非线性模型,且具有输出诱导时延的一类网络控制系统（NCS）,假设可能发生执行器故障,对系统进行故障检测：利用T—S模糊模型将对象线性化,建立了模糊观测器,并给出了观测器系统渐近稳定的条件。进一步地,又考虑到满足该观测器稳定条件的矩阵难以寻找到,因此利用模糊模型中的主导子系统思想,重新设计了观测器,并基于Lyapunov稳定性定理,推导出了整个观测器系统全局渐近稳定的充分条件。最后,通过一个仿真例子验证了方法的有效性。     

State and Unknown Input H∞ Observers for Discrete‐Time LPV Systems

This paper proposes state and unknown input (UI) observers for linear parameter varying (LPV) systems affected by UI and perturbations in both state and measurement equations. The estimation is done by minimizing the L₂ transfer between the perturbations and the state estimation error (H_∞‐observation). The originality of the paper is to provide a generalization of existing works, specially by relaxing an assumption on systems matrices, widely used for UI decoupling. After giving the main results, some examples illustrate the theoretical contributions and give comparisons to former publications.     

Adaptive Non‐Backstepping Fuzzy Control for a Class of Uncertain Nonlinear Systems with Unknown Dead‐Zone Input

Based on the approximation property of fuzzy logic systems, we propose a novel non‐backstepping adaptive tracking control algorithm for a class of single input single output (SISO) strict‐feedback nonlinear systems with unknown dead‐zone input. In this algorithm, we introduce some novel state variables and coordinate transforms to convert the strict‐feedback form into a normal one, and it is not necessary to consider the traditional approximation‐based the backstepping scheme. Due to new states variables being unavailable, the tracking control is changed from a state‐feedback one to an output‐feedback one. So, observers need to be designed to estimate the indirect nonmeasurable states. According to Lyapunov stability analysis method, the developed controller can guarantee that all of the signals in the closed‐loop system will be ultimately uniformly bounded (UUB), and the output can track the reference signal very well. Simulation results are presented to show the effectiveness of the proposed approach.     

AGC系统中的非线性观测器设计

AGC（自动发电控制）系统是一个十分复杂的系统，其具有严重的非线性，且输入（锅炉、轮机等动力产生部分）和输出（频率负载）均存在未知扰动，为了实现对发电系统的精确控制，设计出输入输出扰动的观测器显得尤为重要。在阐述了一种带有未知输入输出扰动的非线性观测器设计方法的同时，是对传统的只能观测输入环节中的未知扰动观测器的一大改进。通过对系统状态方程和输出方程的一系列解偶变换，将输入、输出扰动从系统中分离出来。解偶后，系统分为受扰子系统和无扰动子系统两部分，通过对无扰动子系统的分析，最终设计出输入输出未知扰动观测器。系统观测器增益矩阵则通过求解一个代数Riccati方程（ARE）得到。将设计出的观测器用于故障检测与隔离（FDI）并取得良好的效果。     

复杂工业过程质量相关的故障检测与诊断技术综述

质量相关的故障检测与诊断技术是保证安全生产及获得可靠产品质量的有效手段,是当前国际过程控制领域的研究热点.首先,梳理了质量相关的故障检测技术中典型方法的基本思想和改进过程;其次,概述了质量相关的故障诊断技术中常用的贡献图法及其相关改进方法之间的联系,并通过带钢热连轧过程（Hot strip mill process,HSMP）案例比较了各种典型方法在质量相关的故障检测与诊断性能上的异同;最后,面向复杂工业过程运行数据的主要特性,评析了质量相关的故障检测与诊断方法的研究现状,并指出了该研究领域亟需解决的问题和未来的发展方向.     

Unknown input reconstruction for LPV systems

Detection and invariant subspaces of unknown inputs' signals for linear parameter‐varying systems are examined in the paper. For a class of nonlinear system like this, the effect of unmeasured signals in parameter‐varying measurement equation at the plant output is investigated. The main contributions of the paper are the parameter‐varying extension of the pseudo‐actuation of the possible and generic unknown sensor signal and the proposition of parameter‐dependent similarity transformation. The general parameter‐varying measurement equation is casted into a parameter‐independent form by the similarity transformation, if any. Moreover, it showed that the nonlinear state transformation does not modify the output subspace spanned by the equivalent pseudo‐actuator directions. The proposed methods are illustrated by a numerical example. Copyright © 2009 John Wiley & Sons, Ltd.