匹配条件不满足时线性系统未知输入观测器设计

针对一类不满足观测器匹配条件的线性系统,讨论了未知输入观测器设计方法.首先,为了突破观测器匹配条件的限制,提出了一种与未知输入相对阶无关的辅助输出构造方法.然后,把未知输入看作系统状态的一部分,将原系统转化为一个不含未知输入的增维线性描述系统.针对这样的系统转化,对一系列等价前提条件进行了详细的讨论.之后,针对该增维线性描述系统,构造Luenberger观测器来估计原系统的状态和未知输入.同时,借助于高阶滑模微分器,来估计辅助输出中的未知信号.最后,对一个单连杆柔性机械手模型进行了数值仿真,仿真结果表明了方法的有效性.     

基于自适应滑模观测器的不匹配非线性系统执行器故障重构

针对一类含有未知干扰的不匹配非线性Lipschitz系统,提出了基于自适应滑模观测器的执行器故障重构方法.首先引入辅助输出矩阵,使得辅助输出系统的观测器匹配条件得以满足,同时设计了高增益观测器实现对未知辅助输出的精确估计;然后针对辅助输出系统建立故障重构滑模观测器,设计了自适应律在线修正滑模控制器增益,考虑故障上界未知的前提下,提出了观测器状态估计误差稳定的存在定理,运用Schur补引理将观测器反馈增益矩阵设计方法转化为求解线性矩阵不等式约束优化问题,同时引入线性变换矩阵,在故障上界未知的前提下设计了滑模控制增益,使得输出估计误差收敛稳定,确保了滑模运动在有限时间内发生,在此基础上利用等效控制输出误差注入原理实现了执行器故障重构;最后通过仿真算例验证了本文方法的有效性.     

基于高阶滑模观测器的状态和未知输入同时估计方法

对一类含有未知输入的仿射非线性系统,讨论了一种能同时估计系统状态和末知输入的未知输入观测器设计方法.首先利用李导数对仿射非线性系统进行线性化,将其转化为可控标准型.其次,针对变化后的等价系统,提出了一种高阶、高增益滑模观测器,由此不仅能得到系统状态的估计,同时还得到状态微分的估计.再次,基于状态及其微分的估计,对未知输入提出了一种重构方法.该方法能对强时变未知输入重构,而且重构中没有用到系统微分的信息.最后,通过对两个实际模型的仿真,表明了方法的可行性.     

一种新颖的鲁棒模糊滑模观测器设计及干扰重构方法

针对一类由T-S模糊模型描述的不确定非线性系统,提出一种新颖的鲁棒模糊滑模观测器设计和干扰重构方法.首先,给出一种T-S模糊模型的等价形式.其次,在考虑滑模匹配条件不满足、状态不可测的情况下,利用高增益估计器构造辅助变量.为避免其峰化问题,提出基于高增益估计器的鲁棒滑模观测器.然后,基于所提出的等价形式,给出一类不确定非线性系统的鲁棒模糊滑模观测器设计方法.并证明其不但对系统的未知干扰具有鲁棒性,而且能保证状态估计残差在有限的时间内收敛于任意小的邻域,并可应用等价输出误差介入原理重构出系统的干扰.最后,将该方法应用于双关节机械臂的控制仿真实验.结果表明所提方法的有效性.     

状态估计与未知输入和可测噪声同时重构方法

针对一类不确定线性系统,讨论了状态估计及未知输入和可测噪声重构方法。首先,对仅具有未知输入的线性系统,讨论了观测器匹配条件不满足前提下的状态估计和未知输入重构问题;通过设计降维观测器和高阶滑模观测器,提出一种未知输入代数重构方法;然后,将以上结论上升到具有未知输入和可测噪声的线性系统,以此提出了状态估计及未知输入和可测噪声同时重构的方法;最后,通过对飞行器模型进行仿真,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.     

一类非最小相位系统未知频率正弦干扰的观测器设计

近年来,前馈补偿技术得到广泛研究,其可以提高系统的控制精度.对于非最小相位系统,很难给出干扰和可测信息的直接关系,此外,频率的不确定性以及估计值之间的耦合会导致大量冗余参数的运算.现有的自适应方法存在估计值之间的耦合,会增加干扰估计误差收敛性能分析难度.而基于干扰观测器控制(DOBC)通过调节控制器和观测器参数,可以同时对多源不确定进行补偿和抑制.基于此,提出一种分步式观测器设计方法.首先设计一种辅助滤波器和观测器对未知频率正弦干扰参数进行估计,同时给出干扰的等效形式;然后利用估计值构造观测器得到输入干扰状态,从而将这类非线性系统的干扰抵消问题转换为线性系统的观测器设计问题;最后通过李雅普诺夫定理和数值仿真验证所提出方法的有效性.     

含未知输入的广义系统的状态与输入估计

研究了含未知输入的广义系统的输入解耦观测器设计问题. 在系统脉冲能控的条件下通过系统输入-状态对的非奇异变换, 把此问题等价地转化为正常状态空间系统的相应问题. 用大家熟知的方法设计正常状态空间系统的观测器, 从而得到广义系统的输入解耦观测器. 然后用广义系统的观测器状态和系统输出的线性组合渐近估计系统的状态与未知输入.     

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.     

无未知参数先验信息的非线性自适应观测器设计

研究了一类具有未知参数的非线性系统自适应观测器设计问题.不同于现有结果,本文所研究的非线性系统更为一般,已知的系统信息更少:1)系统未知参数的范数的上界未知;2)具有关于可测输出非Lipschitz连续的非线性动态:3)系统输出显式地依赖于控制输入.通过设计自适应调节器来估计未知参数范数,从而给出了不基于未知参数先验信息的非线性自适应观测器设计的新方法.所设计的观测器为全局渐近收敛的,即实现了系统状态的渐近重构,确保了未知参数估计的一致有界性.此外,在系统输出不显式地依赖于控制输入的条件下,研究了降维观测器的设计问题.仿真例子验证了本文理论结果的正确性.     

State estimation and unknown input reconstruction via both reduced-order and high-order sliding mode observers

This paper considers the problems of the simultaneous estimation of the system states and the unknown inputs for linear systems when the so-called observer matching condition is not satisfied. An auxiliary output vector is introduced so that the observer matching condition is satisfied with respect to it. A high-order sliding mode observer is considered to get the exact estimates of both the auxiliary outputs and their derivatives in a finite time based on the system measured outputs. After this, a reduced-order observer is constructed by using the estimated auxiliary outputs as the new system outputs. The reduced-order observer is able to asymptotically estimate the system states without suffering the influence of the unknown inputs. A kind of unknown input reconstruction method based on both the state and the auxiliary output derivative estimates is developed. Finally, a numerical simulation example is given to illustrate the effectiveness of the proposed methods.     

Sliding-mode observers for systems with unknown inputs: A high-gain approach

Sliding-mode observers can be constructed for systems with unknown inputs if the so-called observer matching condition is satisfied. However, most systems do not satisfy this condition. To construct sliding-mode observers for systems that do not satisfy the observer matching condition, auxiliary outputs are generated using high-gain approximate differentiators and then employed in the design of sliding-mode observers. The state estimation error of the proposed high-gain approximate differentiator based sliding-mode observer is shown to be uniformly ultimately bounded with respect to a ball whose radius is a function of design parameters. Finally, the unknown input reconstruction using the proposed observer is analyzed and then illustrated with a numerical example.     

Sliding-mode observers for nonlinear systems with unknown inputs and measurement noise

This paper deals with the design of observers for Lipschitz nonlinear systems with not only unknown inputs but also measurement noise when the observer matching condition is not satisfied. First, an augmented vector is introduced to construct an augmented system, and an auxiliary output vector is constructed such that the observer matching condition is satisfied and then a high-gain sliding mode observer is considered to get the exact estimates of both the auxiliary outputs and their derivatives in a finite time. Second, for nonlinear system with both unknown inputs and measurement noise, an adaptive robust sliding mode observer is developed to asymptotically estimate the system’s states, and then an unknown input and measurement noise reconstruction method is proposed. Finally, a numerical simulation example is given to illustrate the effectiveness of the proposed methods.     

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.     

Variable high-gain disturbance observer design with online adaption of observer gains embedded in numerical integration

In this paper, a variable gain design approach for the high-gain disturbance observer, called Proportional-Integral-Observer (PI-Observer), is proposed to solve the problem of choosing suitable observer gains. The high-gain PI-Observer is successfully applied to estimate unknown inputs of systems together with the system states. It is known that reasonable estimations of unknown inputs can only be derived using high observer gains. On the other hand, extremely large gains will cause serious problems with respect to measurements noise and unmodeled dynamics. According to the analysis of the estimation quality regarding to the factors which influence the estimation results, the optimal level of observer gains is changing during the estimation, an online adaption for the observer gains is therefore developed. The designed PI-Observer, called Advanced PI-Observer (API-Observer), will use changing observer gains from the adaption algorithm, which is proved to give stable estimation error dynamics. Simulation results from an elastic beam example are shown to illustrate the implementation of the API-Observer.     

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.     

一类非线性系统的自适应观测器设计

在故障诊断应用中, 状态方程中的未知参数和输出方程中的未知参数分别表征执行机构故障和传感器故障, 所以研究状态方程和输出方程同时含有未知参数的自适应观测器有着实际的应用意义. 本文基于高增益观测器和自适应估计理论, 针对状态方程和输出方程同时含有未知参数的一类一致可观的非线性系统, 用构造性方法设计了一种联合估计状态和未知参数的自适应观测器. 该自适应观测器的参数估计采用时变增益矩阵, 结构形式及参数设置简单. 给出了使该自适应观测器满足全局指数收敛性的持续激励条件, 并在理论上简洁地证明了该自适应观测器的全局指数收敛性. 数值仿真结果表明该自适应观测器具有良好的快速收敛性、跟踪性等期望性能.     

Nonlinear sliding mode high-gain observers for fault estimation

A robust high gain observer for state and unknown inputs/faults estimations for a special class of nonlinear systems is developed in this article. Ensuring the observability of the faults/unknown inputs with respect to the outputs, the faults can be estimated from the sliding surface. Under a Lipschitz condition for the nonlinear part, the high gain observers are designed under some regularity assumptions. In the sliding mode, the convergence of the estimation error dynamics is proven similar to the analysis of high-gain observers.