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。     

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.     

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.     

多故障并发非线性系统一体化跟踪主动容错控制器设计

针对一类执行器及传感器同时发生故障的非线性系统,综合鲁棒滑模重构观测器及自适应滑模容错控制器设计技术,提出一体化跟踪主动容错控制方案.首先,将系统增维变换为广义系统,运用广义约束逆引入辅助矩阵,采用线性矩阵不等式设计观测器系数矩阵,综合自适应律给出广义鲁棒滑模观测器设计程式;在此基础之上,通过设计鲁棒滑模微分器估计输出向量微分,结合广义鲁棒滑模观测器状态估计结论,实现执行器及传感器故障同时重构.其次,基于故障重构及状态估计结论,提出自适应滑模的跟踪主动容错控制律设计程式.最后,通过开展飞行模拟转台伺服系统数值仿真,检验一体化跟踪主动容错控制器设计方法的有效性.     

延迟不确定马尔科夫跳变系统的执行器和传感器故障同时估计方法

针对具有参数不确定和延迟环节的马尔科夫跳变系统,在状态转移概率矩阵（Transition probability matrix,TPM）不确定的情形下,讨论了其执行器和传感器故障同时估计的方法.通过扩展系统状态,将系统转换为一个具有马尔科夫跳变参数的广义描述系统,基于此广义描述系统设计马尔科夫跳变观测器实现对其状态和传感器故障的估计.与此同时,还设计了一组自适应律对执行器故障进行在线调节.通过求解一组线性矩阵不等式最优化问题,得到观测器存在的充分条件.最后,针对两个数值实例,验证了所设计方法的有效性.     

基于广义未知输入观测器的鲁棒故障估计方法

当干扰存在时,有效地估计故障且放松故障的限制条件需要进一步的研究,为此针对含未知干扰的非线性连续系统的鲁棒故障估计问题提出一种广义未知输入观测器方法。首先,将执行器故障向量和传感器故障向量与原系统状态向量组成广义系统,放松对故障类型的限制,对此广义系统设计未知输入观测器解耦干扰,保证鲁棒性的同时估计出状态变量、执行器故障及其一阶微分和传感器故障。然后通过解线性矩阵不等式（LMI）给出估计误差渐近收敛的条件。最后,在MATLAB 的simulink平台上用三叶片水平轴风力模型仿真验证本文观测器的故障估计有效性鲁棒性。     

一类受扰线性采样数据系统的鲁棒执行器故障估计

针对一类含有外部干扰的线性采样数据系统, 本文研究了执行器故障估计问题. 首先, 文章设计了一种用于估计系统执行器故障的鲁棒故障估计观测器, 在连续采样时间间隔内, 观测器增益矩阵指数变化. 之后, 通过联合增广状态估计误差与故障误差, 并利用Lyapunov-Krasovskii泛函和线性矩阵不等式技术, 给出了保证误差系统全局渐近稳定的充分条件. 同时, 建立的线性矩阵不等式条件涉及调谐参数和最大采样间隔, 可以较好改善状态和故障估计性能. 最后, 通过对某型民航飞机模型实例进行仿真, 验证了本文所提方法具有更好的跟踪效果     

基于LMI的一体化鲁棒主动容错控制器设计

针对一类发生执行器故障的非线性系统,提出基于线性矩阵不等式(LMI)的一体化鲁棒主动容错控制器设计方法.首先,设计含自适应律的鲁棒滑模观测器,并将观测器设计方法转化为LMI约束下的凸优化问题,进而实现执行器故障的鲁棒重构;然后,提出基于状态及故障估计的一体化主动容错控制器,同时通过LMI给出控制器增益解算方法;最后,通过数值算例验证容错控制器设计方法的有效性.     

汽车稳定控制系统执行器与传感器故障诊断与估计

汽车稳定控制系统具有明显的非线性特性,对其传感器与执行器的故障诊断具有一定难度。从汽车八自由度模型入手,简化模型并建立虚拟输入。针对虚拟输入模型,将虚拟执行器故障作为增广状态向量的一部分,构造一个增广系统。利用李雅普诺夫理论设计观测器,获得原系统状态与虚拟执行器故障的渐近估计,并分析了增广观测器的稳定性与收敛性。通过LMI技术实现线性矩阵不等式求解,完成观测器设计。选择一个新的状态变量作为输出信号滤波器,将传感器故障转化为执行器故障,建立二增广系统,直接利用执行器故障诊断方法实现传感器故障诊断。通过Simulink,验证了此方法的可行性。与其他方法相比,该方法不仅能够同时得到虚拟执行器与传感器故障信号,为系统提供警示,而且为后续的容错控制设计提供可靠数据。     

基于自适应奇异观测器的连续系统故障诊断

针对连续系统的传感器与执行器故障诊断问题,提出一种自适应奇异观测器来进行故障估计,能同时估计系统中的传感器故障与执行器故障,并克服了以往研究中对故障、故障导数与系统干扰作上界已知假设的不足;利用H∞性能指标抑制了干扰对故障估计的影响;通过线性矩阵不等式来获得自适应奇异观测器的增益阵,从而很方便地完成故障诊断观测器的设计;采用Lyapunov泛函证明了观测误差动态系统是鲁棒渐近稳定的;最后通过仿真实例验证了所提方法的有效性。     

Observer design for sensor and actuator fault estimation applied to polynomial LPV systems: a riderless bicycle study case

The present paper addresses an observer design for fault estimation applied to polynomial linear parameter varying (LPV) systems. The main contribution corresponds to a design to provide the estimation of both actuator and sensor faults acting on the system, modelled as additive faults taking place at any time and simultaneously, inclusively. The observer design includes a boundary factor in order to guarantee the estimation error convergence to zero despite the fault occurrence. Simulation results showing the effectiveness of the proposed observer by considering a riderless bicycle LPV model, which depends on the translational velocity of the vehicle, are provided.     

A virtual actuator and sensor approach for fault tolerant control of LPV systems

In this paper, a fault tolerant control (FTC) strategy using virtual actuators and sensors for linear parameter varying (LPV) systems is proposed. The main idea of this FTC method, initially developed for LTI systems, is to reconfigure the control loop such that the nominal controller could still be used without need of retuning it. The plant with the faulty actuator/sensor is modified adding the virtual actuator/sensor block that masks the actuator/sensor fault. The suggested technique is an active FTC strategy that reconfigures the virtual actuator/sensor on-line taking into account faults and operating point changes. The stability of the reconfigured control loop is guaranteed if the faulty plant is stabilizable/detectable. The LPV virtual actuator/sensor is designed using polytopic LPV techniques and linear matrix inequalities (LMIs). A two-tank system simulator is used to assess the performance of the proposed method. In particular, it is shown that the application of the proposed technique results in an improvement, in terms of performance, with respect to the LTI counterpart.     

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.     

不确定时滞系统增益型故障的检测与估计

针对一类不确定连续线性定常时滞系统,提出了一种执行器、传感器增益故障的鲁棒检测与估计策略。该类系统含有多状态与输出时滞,状态和输出方程上同时作用有非结构有界未知扰动。在Trunov和Polycarpou方法的基础上,设计了一种新的时滞系统自适应观测器用于检测并估计突变或缓变的增益故障。与Wang等针对线性无时滞不合输出扰动系统的工作相比,该结论更具一般性。理论分析表明,该方法对于未知扰动鲁棒,能够保证故障的估计,状态与输出估计偏差一致有界。数值仿真验证了方法的有效性。     

Distributed observer design for interconnected nonlinear systems with faults and disturbances based on dynamic event conditions

This study investigated the observer design schemes for interconnected nonlinear systems with actuator faults, sensor faults, external disturbances, and limited measured resources. A novel effective distributed estimation scheme is presented for the interconnected nonlinear system to estimate the states, faults, and lumped disturbances, simultaneously. To save communication resources and to improve information utilization, an adaptive event condition is designed in the sensor channel, and the triggered values are utilized to design the observer. Especially, to handle the sensor fault, the output is separated into two parts, and the estimation is realized with the help of a normal one. In the first part of this study, a class of interconnected nonlinear systems with partial loss of effectiveness of sensor fault is considered, and an event-based distributed estimation scheme is established. In the second part, a class of more universal feedback interconnected nonlinear with both partial loss sensor fault and bias sensor fault is investigated. An augment system is formulated by an augmented vector composed of state and sensor faults. And then the estimation scheme is realized by utilizing the presented event-based distributed observer. The convergence abilities of both the two conditions are proved and, finally, the estimation performances of the presented observer are verified by a numerical simulation system and an inverted pendulum system.     

Fault tolerant sliding mode control for T-S fuzzy stochastic time-delay system via a novel sliding mode observer approach

In this paper, a fault estimation and fault-tolerant control problem for a class of T-S fuzzy stochastic time-delay systems with actuator and sensor faults is investigated. A novel sliding mode observer is proposed, which can simultaneously estimate the system states, actuator and sensor faults with good accuracy. Based on the state and actuator fault estimation, a new sliding mode control scheme is developed, which can effectively eliminate the influence of actuator fault. Sufficient conditions for the existence of the proposed observer and fault-tolerant sliding mode controller are provided in terms of linear matrix inequality, and moreover, the reachability of the sliding mode surface can be guaranteed under the proposed control scheme. The propose sliding mode observer and fault-tolerant sliding mode controller can overcome the restrictive assumption that the input matrix of all local modes is the same. Finally, a numerical example is provided to verify the effectiveness of the proposed sliding mode observer and fault-tolerant sliding mode control technique.     

Robust fault and icing diagnosis in unmanned aerial vehicles using LPV interval observers

This paper proposes a linear parameter varying (LPV) interval unknown input observer for the robust fault diagnosis of actuator faults and ice accretion in unmanned aerial vehicles (UAVs) described by an uncertain model. The proposed interval observer evaluates the set of values for the state, which are compatible with the nominal fault‐free and icing‐free operation and can be designed in such a way that some information about the nature of the unknown inputs affecting the system can be obtained, thus allowing the diagnosis to be performed. The proposed strategy has several advantages. First, the LPV paradigm allows taking into account operating point variations. Second, the noise rejection properties are enhanced by the presence of the integral term. Third, the interval estimation property guarantees the absence of false alarms. Linear matrix inequality–based conditions for the analysis/design of these observers are provided in order to guarantee the interval estimation of the state and the boundedness of the estimation. The developed theory is supported by simulation results, obtained with the uncertain model of a Zagi Flying Wing UAV, which illustrate the strong appeal of the methodology for identifying correctly unexpected changes in the system dynamics due to actuator faults or icing.