不确定动态系统的执行器故障检测与重构

讨论不确定动态系统的执行器故障检测与重构问题.以滑模观测器为基础,利用状态和输出变换方法与奇异值分解方法相结合对系统进行降阶,提出一种鲁棒故障重构观测器.给出了优化滑模策略,并作了严格论证,保证对系统不确定性具有鲁棒性和跟踪系统状态的收敛性.应用等价输出控制的概念和设计的鲁棒故障重构观测器,获取故障信息并实现执行器故障的检测与重构.最后通过数值仿真验证了该方法的有效性和可靠性.     

一种基于全维和降维观测器的故障检测和重构方法

针对不确定性非线性系统,讨论基于观测器的执行器故障的检测和重构方法.首先,通过设计滑模全维观测器,产生对干扰具有鲁棒性、对故障具有敏感性的残差,来达到故障检测的目的;然后,设计能直接消去干扰和故障影响的降维观测器来达到状态渐近收敛估计,并在此基础上,提出故障重构方法;基于微分方程的数值解方法和函数微分的数值解方法,给出一种故障重构的数值解方法;最后,对一个实际模型进行仿真,结果表明了该方法的实用性.     

基于高增益鲁棒滑模观测器的故障检测和隔离

针对一类同时具有执行器和传感器故障的不确定线性系统,讨论了基于观测器的故障检测和隔离方法.首先,通过引入增维向量,使得在构造的增维系统中,故障向量包含了原系统的执行器故障和传感器故障.通过构造辅助输出使增维系统的观测器匹配条件得以满足,同时设计高增益滑模观测器对辅助输出进行估计.然后,对增维系统构造鲁棒滑模观测器并用作故障检测观测器,通过滑模控制项来抑制干扰,使观测器具有鲁棒性.在此基础上,结合多观测器故障隔离思想,提出了可以同时对执行器故障和传感器故障进行检测和隔离的方法. 最后,通过对一个五阶飞行器模型进行仿真,证明了所提方法的有效性.     

切换系统激活模式辨识和有限时间状态估计北大核心CSCD

针对一类具有未知输入的不确定线性切换系统,考虑并利用有限时间观测器解决其激活模式辨识和有限时间状态估计问题。首先,利用状态和输出变换得到解耦未知输入的降维切换系统。其次,为每一个降维子系统设计一个对应的有限时间观测器,并对降维系统与观测器系统输出的残差范数进行最小化,从而提出一种激活模式辨识的方法。然后,通过有限时间观测器设置任意小的时间参数,实现了对降维解耦切换系统的有限时间状态估计,同时利用状态等价变化的方法得到原系统的有限时间状态估计。最后,通过MATLAB仿真验证了所提方法的可靠性。     

基于有限时间未知输入观测器的一类受扰非线性系统故障检测与估计

针对一类非线性系统同时存在执行器故障、传感器故障和扰动的问题,提出一种基于有限时间未知输入观测器的故障检测与估计方法.首先,通过线性非奇异变换将原系统解耦为两个降阶的子系统,其中一个子系统只包含扰动,另一个子系统同时包含扰动和故障;然后,通过一阶低通滤波器获得新的状态并与子系统构成增广系统,实现将原系统的传感器故障转化为增广系统的执行器故障;接着,设计未知输入观测器对增广系统故障进行检测,实现在有限时间内估计出系统的扰动和故障,并通过理论分析验证所设计观测器的有限时间收敛性;最后,基于永磁同步电机(PMSM)转速系统进行仿真研究,仿真结果验证了所提出方法的有效性.     

基于滑模观测器和广义观测器的故障估计方法

针对受未知干扰影响的一类非线性系统,提出一种基于滑模观测器和广义观测器的执行器故障和传感器故障估计方法.首先通过线性变换将原系统解耦为两个降阶的子系统,其中一个子系统受执行器故障和干扰的影响,另一个含有传感器故障和干扰,进一步将后一个子系统转化为广义系统.对两类子系统分别设计滑模观测器和广义观测器,给出估计误差一致最终有界的条件,得到系统状态和未知干扰的估计值.然后,利用等效输出控制原理重构执行器故障,引入干扰补偿保证重构算法的鲁棒性,再根据广义观测器的结果获得传感器故障的估计值.最后,通过计算机仿真验证了本文方法的有效性.     

未知输入和可测噪声重构之线性矩阵不等式非线性系统观测器设计

针对一类同时具有未知输入和输出可测噪声的Lipschitz非线性系统,讨论了状态估计、未知输入与可测噪声重构的问题.首先,基于广义系统和线性矩阵不等式的方法设计滑模未知输入观测器,不仅对原系统状态进行渐近估计,而且实现了对系统输出可测噪声的重构;其次,考虑一种鲁棒滑模微分器,实现了广义系统输出向量微分的精确估计,并在此基础上,提出了一种未知信息重构方法,该方法具有避免直接使用系统输出微分信息的优点.最后,对火车牵引拖动系统模型仿真,结果表明该方法不但能够实现对系统状态的估计,而且可以有效重构未知信息.     

不确定切换线性系统状态和未知输入估计方法

针对具有未知输入的不确定切换线性系统, 在平均驻留时间切换下, 讨论其状态和未知输入估计方法. 通过等价变换解耦切换系统的未知输入, 以构造降维切换系统. 进而, 设计切换观测器实现对原系统的状态估计, 并求解具有线性矩阵不等式限制的最优化问题, 得到观测器存在的充分条件. 在基于函数微分数值解方法求得系统输出微分的基础上, 提出一种切换系统未知输入的估计方法. 最后通过一个数值实例验证了所提出方法的有效性.

     

马尔可夫跳变系统基于观测器的有限时间容错控制

针对具有一般不确定转移速率的单边Lipschitz Markovian跳变系统,设计了有限时间故障估计观测器和容错控制器.首先,提出一种自适应的有限时间故障估计观测器,它对未知输入具有鲁棒性,能够同时估计出系统的状态、执行器故障和传感器故障,并确保了误差系统的H_∞有限时间有界.然后,基于所估计的状态和执行器故障,提出一种有限时间故障容错控制方法确保闭环系统H_∞有限时间有界.通过线性矩阵不等式的形式,给出了所设计的有限时间观测器和控制器存在的充分条件.最后,通过一个仿真实例,验证了所提方法的有效性.     

一类非线性系统的故障重构与容错控制

针对一类满足Lipschitz条件的仿射非线性系统,提出一种执行器故障重构与容错控制方法。通过非奇异变化矩阵对系统进行降阶,设计出滑模故障重构观测器,优化滑模策略,使滑模故障重构观测器渐进估计系统的状态,并给出稳定性分析。运用等价输出控制方法直接获取故障信息,实现执行器故障的检测与重构。设计出主动容错控制器,通过补偿控制,完成执行器故障的容错控制。最后通过数值仿真验证了方法的可行性与有效性。     

Full-order observer-based actuator fault detection and reduced-order observer-based fault reconstruction for a class of uncertain nonlinear systems

This paper considers observer-based actuator fault detection and reconstruction problems for uncertain nonlinear systems. Based on a kind of full-order observer which is robust to disturbances but sensitive to actuator faults, a single detection observer is constructed to produce a residual which can be used to alarm the occurrence of the actuator faults when at least one actuator fault occurs indeed. The full-order observer is adaptive one because an adaptation law which can adjust the Lipschitz constant of Lipschitz term is introduced. For this reason, the Lipschitz constant can be unknown in our design. After this, a kind of reduced-order observer is developed by choosing a special observer gain matrix. Based on the reduced-order observer, we provide a kind of unknown information estimating method which can be used to not only reconstruct the actuator faults but also estimate the disturbances of the system. In simulation, a real model of the seventh-order aircraft is used to illustrate the effectiveness of the proposed methods.     

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.     

Fault detection and estimation for a class of PIDE systems based on boundary observers

In this paper, we propose a simultaneous state estimation and fault estimation approach for a class of first‐order hyperbolic partial integral differential equation systems. Specifically, we consider the multiplicative boundary actuator and sensor faults, ie, unknown fault parameters multiplying by the boundary input or boundary state (ie, output). As a consequence, two difficulties arise immediately: (1) simultaneous estimation of both plant state and faults is a nonlinear problem due to the multiplication between fault parameters and plant signals; (2) no prior information is available to determine the type (actuator or sensor) of faults. To overcome these difficulties, this paper develops adaptive fault parameter update laws and embeds the resulting laws into the plant state observer design. First, we propose new approaches to estimate actuator fault and sensor fault, respectively. Next, we develop a novel method to simultaneously estimate actuator and sensor faults. The proposed observer and update laws, designed using only one boundary measurement, ensure both state estimation and fault parameter estimation. By choosing appropriate Lyapunov functions, we prove that the estimates of state and fault parameters converge to an arbitrarily small neighborhood of their true values. Numerical simulations are used to demonstrate the effectiveness of the proposed estimation approaches.     

Integrated design of robust fault estimation and fault‐tolerant control against simultaneous actuator and sensor faults

This paper investigates the problems of simultaneous actuator and sensor faults estimation, as well as the fault‐tolerant control scheme for a class of linear continuous‐time systems subject to external disturbances. First, the original system is transformed into a singular form by extending the actuator fault and sensor fault to be parts of the new state. Then, a new estimation technique named non‐fragile proportional‐derivative observer is designed for the singular system to achieve simultaneous estimations of states and faults. With the obtained estimations information, an integrated design of the non‐fragile output feedback fault‐tolerant controller is explored to compensate for the effect of faults by stabilizing the closed‐loop system. Finally, a simulation study on a two‐stage chemical reactor with recycle streams is provided to verify the effectiveness of the proposed approach.     

基于扩展滤波器的非线性系统迭代学习故障诊断算法

针对一类存在执行器和传感器故障的非线性系统,提出基于滤波器的故障重构方法。为了使算法同时适用于状态和输出端,通过由系统方程构造新状态方程对系统作扩展变换,将原系统输出端非线性和故障转换到扩展系统的状态方程,在此基础上设计故障诊断滤波器,采用迭代学习调节算法更新虚拟故障使之逼近实际故障。该算法可以检测和估计系统故障,并且对不同类型故障具有一定的适应性。在单关节机器人模型上进行仿真实验,实验结果验证了所提出算法的可行性和有效性。     

Robust Sliding Mode Observer based Fault Estimation for Certain Class of Uncertain Nonlinear Systems

This paper proposes a new scheme for estimating the actuator and sensor fault for Lipschitz nonlinear systems with unstructured uncertainties using the sliding mode observer (SMO) technique. Initially, a coordinate transformation is introduced to transform the original state vector into two parts such that the actuator faults only appear in the dynamics of the second state vector. The concept of equivalent output error injection is then employed to estimate the actuator fault. The effects of system uncertainties on the estimation errors of states and faults are minimized by integrating an uncertainty attenuation level into the observer. The sufficient conditions for the state estimation error to be bounded and satisfy a prescribed performance are derived and expressed as a linear matrix inequality (LMI) optimization problem. Furthermore, the proposed actuator fault estimation method is extended to sensor fault estimation. Finally, the effectiveness of the proposed scheme in estimating actuator and sensor faults has been illustrated considering an example of a single‐link flexible joint robot system.