Design and simulation of fault diagnosis based on NUIO/LMI for satellite attitude control systems

This paper presents a scheme of fault diagnosis for flexible satellites during orbit maneuver. The main contribution of the paper is related to the design of the nonlinear input observer which can avoid false alarm arising from the disturbance from orbit control force. The effects of orbit control force on the fault diagnosis system for satellite attitude control systems, including the disturbing torque caused by the misalignments and the model uncertainty caused by the fuel consumed, are discussed, where standard Luenberger observer cannot work well. Then the nonlinear unknown input observer is proposed to decouple faults from disturbance. Besides, a linear matrix inequality approach is adopted to reduce the effect of nonlinear part and model uncertainties on the observer. The numerical and semi-physical simulation demonstrates the effectiveness of the proposed observer for the fault diagnosis system of the satellite during orbit maneuver.     

Novel robust fault diagnosis method for flight control systems

A novel robust fault diagnosis scheme, which possesses fault estimate capability as well as fault diagnosis property, is proposed. The scheme is developed based on a suitable combination of the adaptive multiple model （AMM） and unknown input observer （UIO）. The main idea of the proposed scheme stems from the fact that the actuator Lock-in-Place fault is unknown （when and where the actuator gets locked are unknown）, and multiple models are used to describe different fault scenarios, then a bank of unknown input observers are designed to implement the disturbance de-coupling. According to Lyapunov theory, proof of the robustness of the newly developed scheme in the presence of faults and disturbances is derived. Numerical simulation results on an aircraft example show satisfactory performance of the proposed algorithm.     

一类不确定时延网络控制系统的故障诊断

研究了具有不确定时延的网络控制系统的故障诊断问题。通过建模将一类具有不确定时延的网络控制系统等效为具有不确定性的离散线性系统,并构建了故障观测器对系统进行故障检测。基于线性矩阵不等式(LMI)的方法,将故障诊断问题转化为系统鲁棒性的设计问题,给出并证明了解存在的条件以及观测器增益矩阵的求解方法。最后通过仿真验证了该算法的有效性。     

基于非线性自适应观测器的故障诊断

将自适应控制的思想和状态观测器方法相结合研究了一类非线性控制系统的故障诊断问题。针对一类满足Lipschitz条件的带有未知参数的非线性系统,提出了一种非线性自适应状态观测器的设计方法,并将其应用到控制系统的故障诊断中。通过设置未知故障向量的自适应调整律,保证了状态观测器的渐近稳定。数字仿真证明了该方法的有效性,系统渐近稳定,状态向量和故障向量的估计值均趋近于实际值。     

Robust fault detection for a class of nonlinear network control system with communication delay

To investigate a class of nonlinear network control system, a robust fault diagnosis method is presented based on the robust state observer. To access the objective that the designed robust filter is maximally tolerant to disturbances and sensitive to fault, the robustness and stability properties of the fault diagnosis scheme are established rigorously. Using the residual vector, a fault tolerant controller is established in order to guarantee the stability of the closed-loop system, and the controller law can be obtained by solving a set of linear matrix inequalities. Then, some relevant sufficient conditions for the existence of a solution are given by applying Lyapunov stability theory. Finally, a simulation example is performed to show the effectiveness of the proposed approach.     

Actuator fault diagnosis of time-delay systems based on adaptive observer

1 .INTRODUCTIONOwingtotheincreasing demandfor highreliabilityinmany industrial processes , much attention has beenpaid to the problem of fault detection and diagnosis(FDD) in dynamic systems over the past twodecades. Fruitful results can be found in Refs .[1 ~3] .It is well known that faults in a dynamic systemcan take many forms . They can be actuator faults ,sensor faults ,unexpected abrupt changes of some pa-rameters or even unexpected structure changes[4 ,5].The purpose of detection…     

基于主导子系统的非线性系统鲁棒故障诊断

针对非线性不确定系统的故障诊断问题,提出了一种基于主导子系统的自适应模糊观测器设计方法。利用主导子系统的观测器增益矩阵进行模糊观测器的设计,并推导出了系统状态估计误差有界的条件以及故障估计所要满足的自适应算法。另外,考虑到系统带有建模不确定,对故障检测的鲁棒性和灵敏度进行了分析。给出的仿真示例说明所提出的方法是有效的。     

一类非线性系统的执行器偏差故障诊断

针对一类具有系统建模误差,以及含传感器模型不确定项的非线性控制系统,提出了一种用于执行器故障诊断的观测器方法。观测器中引入自适应补偿项,当出现偏差后将对故障及建模不确定项进行补偿。自适应算法中采用了死区算子,增强了算法的鲁棒性。同时利用自适应律进行偏差估计。理论分析证明观测器的观测误差收敛到零。仿真结果表明了方法的有效性。     

线性时滞系统的鲁棒故障诊断

研究了一类含有未知输入干扰和模型不确定性的时滞系统故障诊断问题。通过变换,原系统被分成两个子系统,一个子系统不受故障的影响,可以设计鲁棒观测器;另一个子系统受到故障的影响,但是它的状态可以通过测量得到。设计的观测器利用解析冗余方法能够对执行器故障和传感器故障进行诊断。仿真结果表明,算法具有良好的诊断性能。     

Fault detection for nonlinear networked control systems based on fuzzy observer

Security and reliability must be focused on control systems firstly, and fault detection and diagnosis (FDD) is the main theory and technology. Now, there are many positive results in FDD for linear networked control systems (LNCSs), but nonlinear networked control systems (NNCSs) are less involved. Based on the T-S fuzzy-modeling theory, NNCSs are modeled and network random time-delays are changed into the unknown bounded uncertain part without changing its structure. Then a fuzzy state observer is designed and an observer-based fault detection approach for an NNCS is presented. The main results are given and the relative theories are proved in detail. Finally, some simulation results are given and demonstrate the proposed method is effective.     

Super-twisting扩张状态观测器在四旋翼飞行器故障重构中的应用

针对四旋翼飞行器姿态控制系统的故障重构问题,提出一种基于super-twisting算法的扩张状态观测器,以扩张状态的形式对飞行器执行机构故障进行直接估计,同时实现了旋翼增益故障的故障隔离与精确重建。为抑制外部扰动对观测器稳定性的影响,一般需要将观测器的增益设置较大,但同时会引发噪声扩展问题。因此引入了观测器参数的自适应调整算法,在保证观测器稳定收敛的同时降低了噪声对故障重构精度的影响。此外,基于李雅普诺夫方法证明了滑模观测器的渐近收敛特性,并通过数值仿真验证了观测器对故障重构的有效性。仿真结果表明所构建的故障观测器能够迅速地对执行机构故障做出反应，并在外界扰动存在的情况下对故障程度实现准确估计。     

Super-twisting扩张状态观测器在四旋翼飞行器故障重构中的应用

针对四旋翼飞行器姿态控制系统的故障重构问题,提出一种基于super-twisting算法的扩张状态观测器,以扩张状态的形式对飞行器执行机构故障进行直接估计,同时实现了旋翼增益故障的故障隔离与精确重建。为抑制外部扰动对观测器稳定性的影响,一般需要将观测器的增益设置较大,但同时会引发噪声扩展问题。因此引入了观测器参数的自适应调整算法,在保证观测器稳定收敛的同时降低了噪声对故障重构精度的影响。此外,基于李雅普诺夫方法证明了滑模观测器的渐近收敛特性,并通过数值仿真验证了观测器对故障重构的有效性。仿真结果表明所构建的故障观测器能够迅速地对执行机构故障做出反应，并在外界扰动存在的情况下对故障程度实现准确估计。     

基于T-S模糊模型的鲁棒故障诊断

针对T-S模糊模型描述的具有外部干扰的非线性不确定系统,构造了相应的测量冗余方程和模糊奇偶方程,给出并证明了对特定传感器和执行器故障敏感的最优奇偶向量的存在条件和求解定理,采用奇偶方程故障检测与诊断方法,研究了非线性不确定系统的鲁棒故障检测和诊断.最后,通过仿真示例说明了所提出的方法是有效的.     

连续广义系统的未知输入观测器研究

研究了在未知输入下连续广义系统的降阶观测器的设计方法,并讨论了观测器在故障检测中的应用。首先给出了连续估计器的存在条件,通过给原系统加微分反馈实现正则化,又通过解耦变换使得只有一个状态向量含有未知输入,利用其余两个不受未知输入影响的状态向量设计出观测器。然后,假设未知输入为故障信号的情况下,利用观测器的方法研究了连续广义系统的故障检测问题。仿真结果显示了满意的估计性能。     

Distributed Finite-Time Integral Sliding-Mode Control for Multi-Agent Systems with Multiple Disturbances Based on Nonlinear Disturbance Observers

This paper proposes a finite-time consensus control algorithm based on nonlinear integral sliding-mode control for second-order multi-agent systems(MASs) with mismatched and matched disturbances. Firstly, a nonlinear finite-time disturbance observer is established to estimate the states and mismatched disturbances of the agent. Secondly, a dynamic integral sliding-mode(ISM) surface is designed by employing the estimates of mismatched disturbances. Then, based on the designed ISM and disturbance observer, the discontinuous or continuous campsite control protocols are respectively developed to guarantee the consensus for MASs in finite time with active anti-disturbance control. Finally,numerical simulation results illustrate the effectiveness of the proposed consensus control algorithm.     

基于自适应神经网络的非线性系统故障诊断

针对一类模型未知及状态不可测的非线性系统,提出了基于自适应神经网络的故障诊断策略,不仅在线估计神经网络的矩阵权重,而且在线估计高斯函数的宽度和中心。该方法对系统的未知非线性特性没有特别要求,仅对神经网络提出较弱的假设条件。首先利用径向基函数(Radial Basis Function,简称RBF)神经网络构造状态观测器,估计系统的状态。然后利用另一个自适应RBF神经网络作为故障估计器,其输入是系统的估计状态(而不是系统状态),其输出为系统所发生的故障模型。利用Lyapunov稳定理论详细分析了状态误差和故障误差的收敛性,分别给出了两个神经网络的参数调整律,仿真证明了该方法的实用性和有效性。     

基于电压增量的非线性模拟电路软故障诊断

基于节点电压增量关系方程理论,根据高阶故障对低阶故障的覆盖性,并结合替代原理,提出了一种可以诊断非线性模拟电路软故障的字典法,将仅应用于线性模拟电路软故障诊断的方法推广到了含有少量非线性元件的模拟电路。将非线性元件作为一个整体,利用节点电压增量关系方程的线性相关系数作为统一故障特征,实现了电路中非线性元件和线性元件集的硬故障、软故障、单故障和多故障的诊断。给出了含有单个或多个非线性元件的电路诊断方法,并用最小距离法对容差做了相应的处理,最后通过仿真实例证明了该诊断方法的有效性。     

Research on improved integrated FDD/FTC with effectiveness factors

This paper investigates the integrated fault detection and diagnosis(FDD) with fault tolerant control(FTC) method of the control system with recoverable faults.Firstly,a quasi-linear parameter-varying(QLPV) model is set up,in which effectiveness factors are modeled as time-varying parameters to quantify actuators and sensors faults.Based on the certainty equivalency principle,replacing the real time states in the nonlinear term of the QLPV model with the estimated states,the parameters and states can be estimated by a two-stage Kalman filtering algorithm.Then,a polynomial eigenstructure assignment(PEA) controller with time-varying parameters and states is designed to guarantee the performance of the system with recoverable faults.Finally,mathematical simulation is performed to validate the solution in a satellite closed-loop attitude control system,and simulation results show that the solution is fast and effective for on-orbit real-time computation.     

Backstepping-based active fault-tolerant control for a class of uncertain SISO nonlinear systems

Active fault-tolerant control is investigated for a class of uncertain SISO nonlinear flight control systems based on the adaptive observer, feedback linearization and backstepping theory. Firstly an adaptive observer is constructed to estimate the fault in the faulty system. A new fault updating law is presented to simplify the assumption conditions of the adaptive observer. The asymptotical stability of the observer and the uniform ultimate boundedness of the fault estimation error are guaranteed by Lyapunov theorem. Then a backstepping-based active fault-tolerant controller is designed for the faulty system. The asymptotical stability of the closed-loop system and uniform ultimate boundedness of the tracking error are proved based on Lyapunov theorem. The effectiveness of the proposed scheme is demonstrated through the numerical simulation of a flight control system.     

Research and application of hierarchical model for multiple fault diagnosis

1.INTRODUCTION Failureanalysisanddiagnosisoflarge scalesystems havereceivedconsiderableattentionduringtherecent years[1～3].Thesesystemshaveevolvedfromthepre viousonesbasedonheuristicknowledgeofsymptom faultassociationstothemorerecentonesbasedon structure,behaviorandfunctionalityofthedevice andsubsystemtobediagnosed[4].Inthecaseof complexsystem,theapplicationofmodel baseddiag nosisalgorithmsbecomescomputationallyverydiffi cultorevenintractable.Ahierarchicaldiagnosisap proachcansignificant…