设计高阶PI观测器对线性系统故障作鲁棒检测

针对具有干扰的线性定常系统,研究了基于高阶PI观测器的鲁棒故障检测设计问题.基于Sylvester矩阵方程的参数化解,给出了干扰与残差解耦的充要条件,并提出了基于高阶PI观测器的线性系统鲁棒故障检测参数化设计方法.数值算例及仿真分析表明所提鲁棒故障检测参数化设计方法是有效的.     

具有输入饱和的近空间飞行器鲁棒控制

针对近空间飞行器这一类存在外部扰动,输入饱和和参数不确定的多输入多输出线性系统,提出了一种基于干扰观测器的抗饱和鲁棒控制方案.将干扰观测器与抗饱和控制技术相结合,从而消除系统存在的未知外部扰动、输入饱和和不确定性对系统控制的影响.首先,设计干扰观测器对线性外部系统产生的未知扰动进行估计.然后根据干扰观测器输出,通过超前抗饱和方法设计抗饱和补偿器,并将其加入到鲁棒控制器的设计中,保证闭环系统存在输入饱和、未知外部扰动和参数不确定情况下的稳定性.为便于设计,干扰观测器、抗饱和补偿器和控制器设计矩阵均通过求解线性矩阵不等式得到.最后,将提出的鲁棒抗饱和控制方法应用于近空间飞行器,仿真结果验证了该控制方案的有效性.     

基于观测器的多智能体系统一致性控制与故障检测

针对一类受到未知干扰的非线性多智能体系统,提出了一种鲁棒一致性控制与故障检测算法.首先,针对每个智能体系统设计了一个未知输入非线性观测器.然后,基于观测器的状态估计信息,设计了鲁棒一致性控制协议.控制协议保证了给定的干扰抑制性能指标.接着,考虑智能体出现故障的情形,采用自适应阈值法,提出了一种分布式故障检测算法.最后,以多个直流电机驱动的单摆系统为例进行了仿真实验,仿真结果表明了一致性控制与故障检测算法的有效性.     

基于鲁棒滑模观测器的多电机卷绕系统故障检测和隔离

针对多电机卷绕系统故障检测和隔离问题,提出了基于滑模观测器的鲁棒故障检测和隔离策略.首先,考虑到多电机卷绕系统运行环境变化引起的摩擦系数、杨式模量、半径和转动惯量等参数的不确定性,通过引入非线性未知输入干扰对系统不确定参数进行描述,将多电机卷绕系统转化为包含执行器故障的一般不确定非线性系统;其次,构造鲁棒滑模观测器并用作故障检测观测器,通过滑模控制来抑制未知输入干扰,使观测器具有鲁棒性,在此基础上,结合多观测器故障隔离的思想,提出了可以同时对多个执行器故障进行检测和隔离的方法;然后,根据李雅普诺夫理论得到使观测器系统指数收敛的充分条件,同时给出了观测器增益的求解方法;最后,仿真结果验证了所提方法的鲁棒性和有效性.     

一类伴有部分解耦干扰的非线性系统故障诊断

针对Lipschitz非线性系统执行器故障检测和传感器故障估计问题,本文提出了一种基于H-/L_∞未知输入观测器的有限频域故障诊断策略.首先,将系统处理成包含传感器故障的增广系统.然后,将该系统的未知输入干扰分为可解耦与不可解耦两部分.针对可解耦部分,利用观测器匹配条件将其从估计误差中消除.针对不可解耦部分,设计L_∞指标抑制其对残差的影响并结合有限频域H-指标提高执行器故障检测灵敏度.接着,给出观测器存在的充分条件并将其转化为受LMIs约束的线性优化问题,实现了执行器故障的鲁棒检测及传感器故障的鲁棒估计.最后,结合仿真算例验证了所提方法的正确性与有效性.     

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。     

LPV鲁棒故障观测器设计

针对线性参数变化（Linear Parameter Varying,LPV）系统的故障检测问题,采用H_- / H_∞混合优化方法,对基于LPV模型的鲁棒故障观测器（RFDO）进行设计,基于离散的参数依赖李亚普诺夫函数,得到了系统的LPV鲁棒故障观测器的综合条件,经过转化,观测器的设计问题被转化为一组线性矩阵不等式的求解问题;利用LMI工具求解线性矩阵不等式,得到了系统的LPV鲁棒故障观测器。最后,通过在一点上对故障输入的非线性仿真,验证了该方法的有效性。     

测量丢失概率不确定的网络化系统的鲁棒故障检测

研究一类具有测量数据丢失概率不确定的网络化系统的鲁棒故障检测问题,系统用概率属于一个区间的Bernoulli随机二进制切换序列来描述测量数据丢失.设计一个基于观测器的鲁棒故障检测滤波器(RFDF),对于区间内的每一个概率,RFDF残差误差输出对故障敏感且对具有L2有界的未知干扰输入有一定的鲁棒性,应用线性矩阵不等式方法,给出并证明了此RFDF的存在条件.最后通过例子说明了该方法的有效性.     

基于未知输入观测器的直流电机鲁棒故障估计

针对直流电机系统提出一种基于未知输入观测器(UIO)的鲁棒故障估计方法,同时估计系统中的执行器故障和传感器故障。首先,构建包含系统传感器故障的增广状态系统;然后,基于该增广系统提出一种新颖的UIO,并给出了该观测器的存在条件和多故障估计策略;同时,引入H_∞性能指标最大程度地抑制干扰对故障估计结果的影响;接着,给出观测器的设计条件和参数求解过程并将其转化为易于求解的线性矩阵不等式(LMI)的形式;最后,通过算例仿真和实验验证了该方法的有效性和可用性。     

基于滑模观测器的临近空间飞行器容错控制

针对临近空间飞行器中结构未知的执行器故障,提出一种基于滑模观测器的容错控制方法。采用Edwards-Spurgeon观测器结构设计滑模观测器,实现对执行器故障的鲁棒估计。根据所得的故障信息设计模型参考滑模容错控制器,控制律的非线性增益分为两部分,保证系统的鲁棒容错性能。一部分利用参数不确定的界值条件设计,一部分基于鲁棒故障估计信息设计。基于李雅普诺夫稳定性理论证明了系统的渐近稳定性。仿真结果表明,该方法能有效实现对执行器故障的鲁棒估计,并保证故障条件下飞行器对参考模型的稳定跟踪性能,达到了期望的容错效果。     

Design of unknown input functional observers for nonlinear systems with application to fault diagnosis

This paper considers the design of low-order unknown input functional observers for robust fault detection and isolation of a class of nonlinear Lipschitz systems subject to unknown inputs. The proposed functional observers can be used to generate residual signals to detect and isolate actuator faults. By using the generalized inverse approach, the effect of the unknown inputs can be decoupled completely from the residual signals. Conditions for the existence and stability of reduced-order unknown input functional observer are derived. A design procedure for the generation of residual signals to detect and isolate actuator faults is presented using the proposed unknown-input observer-based approach. A numerical example is given to illustrate the proposed fault diagnosis scheme in nonlinear systems subject to unknown inputs.     

On-line fault detection in uncertain nonlinear systems using diagnostic observers: a survey

The paper discusses the principles of model-based fault detection and isolation (FDI) in nonlinear and time-varying uncertain dynamic systems. Such systems are typical for such complex plants as, for example, in the chemical process industries or in advanced transportation technology. For a model-based fault diagnosis in such situations, robust or even adaptive strategies are needed. In this paper the theory of robust linear observer-based residual generation for FDI is reviewed from a general point of view. The structural equivalence between the parity space approach and observer-based approach is shown in a new simple graphical way by showing that the observer-based FDI concept can easily be transformed into an equivalent extended parity space configuration, without claiming, however, equivalence of the underlying design techniques. The unknown input observer approach known as a most powerful and comprehensive framework for robust residual generation for FDI in uncertain linear systems is extended to classes of nonlinear and time-varying systems. For such plants an adaptive nonlinear unknown input observer scheme is proposed. Finally, appropriate residual evaluation techniques are outlined and suggestions are made to increase the robustness, for instance by using adaptive thresholds.     

Fault detection and isolation design for uncertain nonlinear systems based on full-order,reduced-order and high-order high-gain sliding-mode observers

This paper considers the observer-based fault detection and isolation design problems when the observer matching condition is not satisfied. Based on the relative degree concept, an auxiliary output vector that may satisfy the observer matching condition is constructed. Since the auxiliary output vector contains unknown information, we use a high-order high-gain sliding-mode observer to exactly estimate not only the auxiliary outputs, but also their derivatives in a finite time. Then, an adaptive robust full-order observer is developed to serve as an actuator fault detection observer. For the actuator fault reconstruction purpose, a reduced-order observer is proposed to estimate the system states even if there are some actuator faults and an actuator fault reconstruction method is provided to reach the fault isolation purpose. A numerical simulation example is used to illustrate the effectiveness of the proposed methods.     

奇异Markov跳跃系统的鲁棒故障检测

研究受L2有界未知输入影响的一类奇异Markov跳跃系统的鲁棒故障检测问题。采用基于观测器的故障检测滤波器（FDF）作为残差产生器,将故障检测滤波器的设计归结为随机意义下的H∞滤波问题。推导并证明了问题可解的充分条件,并通过求解线性矩阵不等式得到了故障检测滤波器参数矩阵的解。算例验证了所给算法的有效性。     

Robust fault detection using Luenberger-type unknown input observers-a parametric approach

A new parametric observer-based approach for robust fault detection in multivariable linear systems with unknown disturbances is proposed. The residual is generated through utilizing a Luenberger function observer. By using a parametric solution to a class of generalized Sylvester matrix equations, a parametrization is proposed for the residual generator on the basis of a Luenberger function observer. By further properly constraining the design parameters provided in the Luenberger observer design, the effect of the unknown disturbance is decoupled from the residual signal. The proposed approach provides all the degrees of freedom and is demonstrated to be simple and effective.     

Design and analysis of robust residual generators for systems under feedback control

In this paper, a general approach is presented to design robust fault detection and isolation (FDI) filters for LTI uncertain systems under feedback control. A two-step design procedure is proposed to derive non-conservative robust FDI filters. The first step consists of designing an optimal FDI filter that maximizes fault sensitivity performance and simultaneously minimizes the influence of unknown inputs, for a large class of model perturbations. The design problem is formulated so that all free parameters are optimized via Linear Matrix Inequality techniques. The second step consists of a systematic post-design analysis procedure. A test is proposed to check if all FDI objectives are achieved for all specified model perturbations. The problem is formulated using an appropriate performance index over a specified frequency range. The solution is based on the generalized structured singular value. Finally, experimental results from a pilot laboratory system are presented to demonstrate the effectiveness of the proposed method.     

基于状态观测器的鲁棒故障诊断滤波器设计LMI方法

研究受不确定性扰动影响情况下线性时不变连续时间系统的鲁棒故障诊断滤波器设 计问题.引入一种新的体现残差对于故障信号灵敏度和不确定性扰动鲁棒性的性能指标,从系 统的L2增益角度出发,将基于状态观测器的鲁棒故障诊断滤波器设计问题形成为H∞优化问 题.然后应用线性矩阵不等式技术,给出并证明了该设计问题的解存在条件和求解方法.并通过 简例说明了算法的有效性.     

Sensor fault detection and isolation in a thermal power plant steam separator

A fault detection and isolation approach, specially designed for steam separators in thermal power plants, is presented in the paper. The first step of the proposed algorithm is to identify the process. Because of the presence of sporadic high-intensity measurement noise (outliers), the paper proposes a robust version of recursive identification. Starting from the parameter vector of the identified model, the second step of the proposed procedure has the form of a data-driven fault detector. This particular fault detection and isolation approach was implemented at TEKOB1 Kostolac Thermal Power Plant in Serbia, whose nominal power output is 330 MW.     

模型不确定性线性系统的鲁棒故障检测滤波器设计

基于给定的性能指标函数, 将受模型不确定性和范数有界未知输入影响的线性不确定系统的基于观测器的鲁棒故障检测滤波器设计问题归结为H_∞ 优化问题, 并通过选取适当的后置滤波器和观测器增益矩阵, 使产生的残差达到对于未知输入和模型不确定性的鲁棒性与对于故障的灵敏度的最佳均衡. 简例验证了本文提出算法的有效性.