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。     

基于观测器的无人车H∞预瞄控制器设计

为抑制道路曲率干扰并提高无人车路径跟踪精度,提出一种基于观测器的无人车H_∞预瞄控制器设计方法.首先,将无人车非线性路径跟踪模型转换为线性变参数(linear parameter varying, LPV)系统;然后,建立关于路径曲率的预瞄模型,并将无人车路径跟踪模型与预瞄模型相结合构建增广系统;接着,考虑传感器测量噪声对无人车路径跟踪精度的影响,设计基于观测器的H_∞状态反馈控制器,并将控制器设计问题转化为满足一组线性矩阵不等式的优化问题. Simulink/CarSim联合仿真结果表明,所提出的基于观测器的无人车H_∞预瞄控制方法可以有效减小测量噪声对系统性能的影响,与已有最优控制方法相比,可以取得更好的路径跟踪精度.     

自适应比例–积分H2滑模观测器设计

传统的龙伯格观测器的观测精度极易受到未知外部扰动的影响.为了解决这个问题,本文设计了一种基于径向基神经网络的自适应比例–积分H₂滑模观测器,实现了参数不确定性和外部扰动下非线性系统的鲁棒确切估计.首先,利用径向基神经网络自适应逼近系统模型的复杂非线性项;其次,设计基于误差的线性滑模面,将比例–积分滑模项注入观测器中,使得滑模动态在有限时间内收敛于滑模面,实现对外部扰动和系统模型非线性的完全补偿;最后,基于H₂次优控制和区域极点配置,提出观测器参数自整定方法.通过对单连杆机器人的仿真结果表明,该方法能够保证非线性系统具有较好的鲁棒性和自适应性.     

基于观测器的受扰多项式系统H∞输出跟踪控制

考虑一类受到外部扰动影响的多项式系统在状态不完全可测情况下的H_∞输出跟踪控制问题.首先,综合前馈-反馈复合控制思想,设计基于观测器的输出跟踪控制器,其中反馈镇定控制器用于保证闭环系统稳定,前馈补偿控制器用以实现对参考模型输出信号的跟踪;然后,提出具有输出反馈结构的跟踪控制方法,其优势在于实现了分离原则,可单独设计观测器和控制器,降低计算复杂度;接着,利用依赖全状态的齐次多项式Lyapunov函数导出使得闭环系统渐近稳定且满足H_∞跟踪性能的充分条件,借助多项式平方和凸优化技术可直接求得相应的观测器和控制器;最后,通过数值仿真实例验证所提出设计方法的有效性和优越性.     

一类互联非线性系统的分布式故障估计观测器设计

针对一类互联非线性系统,提出一种分布式故障估计观测器设计方法.首先,将状态向量和故障向量进行增广设计,得出等价的增广互联系统;其次,利用互联子系统之间的耦合信息,设计包含关联子系统估计信息的分布式故障估计观测器,用于在线实时估计子系统中出现的故障;再次,提出基于$H_\infty$性能和$L_2-L_\infty$性能的方法求解观测器增益矩阵;最后,通过一个仿真实验表明所提出方法的可行性和有效性.     

非线性切换系统基于观测器的容错控制器设计

针对一类具有执行器故障的非线性切换系统,研究基于系统状态估计和故障重构的容错控制问题.首先,在具有平均驻留时间(ADT)的切换信号下,设计一种切换PI观测器作为状态-故障估计器,以达到对系统状态和故障同时渐近估计的目的;其次,基于线性矩阵不等式,给出非线性切换系统观测器存在的充分条件;再次,基于PI观测器给出的状态和故障估计,提出一种非线性切换系统的容错控制器设计方法;最后,以一个电子电路为仿真实例进行分析,验证了所提出方法的可行性和适用性.     

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.     

基于区间观测器的执行器故障检测

针对同时具有未知非线性函数(包括系统不确定性、外部干扰等) 和执行器故障的非线性系统, 提出基于区间观测器的故障检测方法. 首先, 在假定执行器故障不出现的前提下, 基于未知非线性函数的上下界信息, 提出两种区间观测器设计方法; 然后, 利用这两种区间观测器的输出和系统的真实输出, 构造可以对执行器故障进行检测的残差, 以此实现基于区间观测器的执行器故障检测. 最后, 通过两个仿真例子验证了所提出方法的正确性和有效性.

     

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。     

修改型扩张状态观测器:分析与实现

利用系统已知信息构造的扩张状态观测器(extended state observer,ESO)称之为修改型扩张状态观测器.本文完善了修改型扩张状态观测器(modified extended state observer,MESO)的假设条件,并分析了相对于常规的扩张状态观测器,修改型扩张状态观测器估计精度更高的原因.针对系统模型参数不确定情况,提出了基于最小二乘法的修改型扩张状态观测器实现方法,并详细论述了最小二乘法在线辨识系统模型的原理.仿真结果与理论分析结果一致,验证了修改型扩张状态观测器理论分析的正确性和实现方法的可行性.     

A modified sliding-mode observer design with application to diffusion equation

In many physical systems, the system's full state cannot be measured. An observer is designed to reconstruct the state from measurements. Disturbances often contribute to the dynamics of the system, and the designed observer must account for them. In this paper, a modified sliding-mode observer (SMO), a robust observer, is proposed that combines the efficiency of a nonlinear observer with the robustness of an SMO. The estimation error is proven to converge to zero under natural assumptions. This improved observer is compared with an extended Kalman filter and an unscented Kalman filter, as well as a standard SMO for three different versions of heat equation: a linear, a quasi-linear, and a nonlinear heat equation. The comparisons are done with and without an external disturbance. The simulations show improved performance of the modified SMO over other observers.     

Second-order sliding-mode observer for mechanical systems

The super-twisting second-order sliding-mode algorithm is modified in order to design a velocity observer for uncertain mechanical systems. The finite time convergence of the observer is proved. Thus, the observer can be designed independently of the controller. A discrete version of the observer is considered and the corresponding accuracy is estimated.     

A stochastic analysis of a modified gain extended Kalman filter with applications to estimation with bearings only measurements

A new globally convergent nonlinear observer, called the modified gain extended Kalman observer (MGEKO), is developed for a special class of systems. This observer structure forms the basis of a new stochastic filter mechanization called the modified gain extended Kalman filter (MGEKF). A sufficient condition for the estimation errors of the MGEKF to be exponentially bounded in the mean square is obtained. Finally, the MGEKO and the MGEKF are applied to the three-dimensional bearings-only measurement problem where the extended Kalman filter often shows erratic behavior.     

Design of a Modified Controller in the State Space

A controller of an object that is designed in the space of states generally consists of two blocks: an observer and a block implementing a control law. The combination of the two blocks to form a unified block (modified controller) permits reducing the computational and the algorithmic complexity of processing the measurable information. Optimality criteria with small parameters are set up, which offer the possibility of designing a modified controller, leaving out the procedure of design of an observer.     

基于改进型滑模观测器的永磁同步电机无位置传感器控制

永磁同步电机无位置传感器控制技术通常使用滑模观测器观测反电动势,进而获取转子位置和速度信息.为提升滑模观测器的性能,本文设计了一种改进型自适应超螺旋滑模观测器.首先,文章在超螺旋滑模观测器结构中增加观测误差的线性项,以提高观测器的动态性能.接着,为解决观测器增益在不同速域下参数不匹配的问题,本文提出一种观测器参数自适应调整策略,提升了观测器参数鲁棒性.在此基础上,采用同步参考系滤波器滤除输出信号的高次谐波,进一步提高观测精度.最后,仿真结果表明,与传统方法相比,本文提出的方法观测性能更好,鲁棒性更强.     

Fault detection in wind turbine transmission systems via finite frequency observers

This paper addresses fault detection for wind turbine transmission system (WTTS) subject to actuator stuck faults and wind disturbances. Taking into account the frequency domain characteristics of such faults and disturbances, a modified observer is designed in terms of finite frequency (FF) performance indices that have detection performances superior to some formerly proposed ones. With the generalized Kalman–Yakubovich–Popov (GKYP) lemma and the Lyapunov theory, the FF performance indices are related to linear matrix inequalities (LMIs), and parametrization of the corresponding FF modified observer is completed by convex optimization under LMI constraints. One typical advantage of the modified observer is that fault and disturbance signals in distinctive FF domains can be dealt with simultaneously. This makes the residual system sensitive to actuator stuck faults and robust against external wind disturbances. Simulations are included to show that the design method achieves fault detection performances better than those of the entire frequency observers.     

A stable neural network-based observer with application to flexible-joint manipulators

A stable neural network (NN)-based observer for general multivariable nonlinear systems is presented in this paper. Unlike most previous neural network observers, the proposed observer uses a nonlinear-in-parameters neural network (NLPNN). Therefore, it can be applied to systems with higher degrees of nonlinearity without any a priori knowledge about system dynamics. The learning rule for the neural network is a novel approach based on the modified backpropagation (BP) algorithm. An e-modification term is added to guarantee robustness of the observer. No strictly positive real (SPR) or any other strong assumption is imposed on the proposed approach. The stability of the recurrent neural network observer is shown by Lyapunov's direct method. Simulation results for a flexible-joint manipulator are presented to demonstrate the enhanced performance achieved by utilizing the proposed neural network observer.     

Optimal observers for systems with colored noises

The problem of optimal full-order observers for continuous-time linear systems with colored process and measurement noises is considered. In such cases, optimal estimation of the state involves augmenting the system, thus a higher-order observer is required. The structure of a full-order observer is assumed and necessary conditions for the optimal observer are derived. The conditions are given for the general case where the intensity of the white-noise component of the measurement noise may be singular. The solution consists of a modified Riccati equation and a Lyapunov equation coupled by two projection matrices in the singular case and one projection matrix in the nonsingular case     

Nonlinear vehicle side-slip estimation with friction adaptation

A nonlinear observer for estimation of the longitudinal velocity, lateral velocity, and yaw rate of a vehicle, designed for the purpose of vehicle side-slip estimation, is modified and extended in order to work for different road surface conditions. The observer relies on a road-tire friction model and is therefore sensitive to changes in the adhesion characteristics of the road surface. The friction model is parametrized with a single friction parameter, and an update law is designed. The adaptive observer is proven to be uniformly globally asymptotically stable and uniformly locally exponentially stable under a persistency-of-excitation condition and a set of technical assumptions, using results related to Matrosov's theorem. The observer is tested on recorded data from two test vehicles and shows good results on a range of road surfaces.