Design and Analysis of Fault Diagnosis and Fault-tolerant Control for a Class of MIMO Nonlinear State Systems

This paper presents a fault diagnosis and fault-tolerant control algorithm,which can be used for a class of multi-input multi-output(MIMO)nonlinear state systems.First,a state estimator is proposed,which is able to detect fault occurrence,by using a residual signal.Second,when the state is at an abnormal condition,the fault-tolerant control will be triggered to minimize the impact of the fault occurrence.This fault-tolerant control is designed by using a robust controller(original controller),and an on-line approximator to capture a nonlinear function that indicates the fault occurrence.The detailed analysis is given for the proposed fault accommodation control.

Rule-based Fault Diagnosis of Hall Sensors and Fault-tolerant Control of PMSM

Hall sensor is widely used for estimating rotor phase of permanent magnet synchronous motor(PMSM). And rotor position is an essential parameter of PMSM control algorithm, hence it is very dangerous if Hall senor faults occur. But there is scarcely any research focusing on fault diagnosis and fault-tolerant control of Hall sensor used in PMSM. From this standpoint, the Hall sensor faults which may occur during the PMSM operating are theoretically analyzed. According to the analysis results, the fault diagnosis algorithm of Hall sensor, which is based on three rules, is proposed to classify the fault phenomena accurately. The rotor phase estimation algorithms, based on one or two Hall sensor(s), are initialized to engender the fault-tolerant control algorithm. The fault diagnosis algorithm can detect 60 Hall fault phenomena in total as well as all detections can be fulfilled in 1/138 rotor rotation period. The fault-tolerant control algorithm can achieve a smooth torque production which means the same control effect as normal control mode (with three Hall sensors). Finally, the PMSM bench test verifies the accuracy and rapidity of fault diagnosis and fault-tolerant control strategies. The fault diagnosis algorithm can detect all Hall sensor faults promptly and fault-tolerant control algorithm allows the PMSM to face failure conditions of one or two Hall sensor(s). In addition, the transitions between health-control and fault-tolerant control conditions are smooth without any additional noise and harshness. Proposed algorithms can deal with the Hall sensor faults of PMSM in real applications, and can be provided to realize the fault diagnosis and fault-tolerant control of PMSM.

An Equipment Fault-tolerant Control Expert System and its Application

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Design and implementation of an expert system for remote fault diagnosis in ship lift

In this paper an expert system for remote fault diagnosis in the ship lift was developed by analysis of the fault tree and combination with VPN. The fault tree was constructed based on the operation condition of the ship lift. The diagnosis model was constructed by hierarchical classification of the fault tree structure, and the inference mechanism was given. Logical structure of the fault diagnosis in the ship lift was proposed. The implementation of the expert system for remote fault diagnosis in the ship lift was discussed, and the expert system developed was realized on the VPN virtual network. The system was applied to the Gaobaozhou ship lift project, and it ran successfully.

Neural network-based fault diagnosis for spacecraft with single-gimbal control moment gyros

This paper proposes a neural network-based fault diagnosis scheme to address the problem of fault isolation and estimation for the Single-Gimbal Control Moment Gyroscopes(SGCMGs)of spacecraft in a periodic orbit.To this end,a disturbance observer based on neural network is developed for active anti-disturbance,so as to improve the accuracy of fault diagnosis.The periodic disturbance on orbit can be decoupled with fault by resorting to the fitting and memory ability of neural network.Subsequently,the fault diagnosis scheme is established based on the idea of information fusion.The data of spacecraft attitude and gimbals position are combined to implement fault isolation and estimation based on adaptive estimator and neural network.Then,an adaptive sliding mode controller incorporating the disturbance and fault estimation results is designed to achieve active fault-tolerant control.In addition,the paper gives the proof of the stability of the proposed schemes,and the simulation results show that the proposed scheme achieves better diagnosis and control results than compared algorithm.

Fault diagnosis and accommodation with flight control applications

This paper reviews some main results and process concerning with fault diagnosis and accommodation with flight control applications.The fault detection and diagnosis including the quantitative and qualitative methods and the fault-tolerant control including passive and active schemes are introduced,respectively.The control designs and developments of the fault diagnosis and accommodation for continuous-time systems and discrete-time systems,the fault diagnosis and fault-tolerant control for switched systems and interconnected systems as well as the applied flight control research including hypersonic vehicle,spacecraft and helicopter systems are summarised.

A review on fault-tolerant cooperative control of multiple unmanned aerial vehicles

This paper presents the recent developments in Fault-Tolerant Cooperative Control(FTCC)of multiple unmanned aerial vehicles(multi-UAVs).To facilitate the analyses of FTCC methods for multi-UAVs.the formation control strategies under fault-free flight conditions of multi-UAVs are first summarized and analyzed,including the leader-following,behavior-based,virtual structure,collision avoidance,algebraic graph-based,and close formation control methods,which are viewed as the cooperative control methods for multi-UAVs at the pre-fault stage.Then,by considering the various faults encountered by the multi-UAVs,the state-of-the-art developments on individual,leader-following,and distributed FTCC schemes for multi-UAVs are reviewed in detail.Finally,conclusions and challenging issues towards future developments are presented.

Active fault-tolerant tracking control of a quadrotor with model uncertainties and actuator faults

This paper presents a reliable active fault-tolerant tracking control system(AFTTCS) for actuator faults in a quadrotor unmanned aerial vehicle(QUAV). The proposed AFTTCS is designed based on a well-known model reference adaptive control(MRAC) framework that guarantees the global asymptotic stability of a QUAV system. To mitigate the negative impacts of model uncertainties and enhance system robustness, a radial basis function neural network is incorporated into the MRAC scheme for adaptively identifying the model uncertainties online and modifying the reference model. Meanwhile, actuator dynamics are considered to avoid undesirable performance degradation. Furthermore, a fault detection and diagnosis estimator is constructed to diagnose lossof-control-effectiveness faults in actuators. Based on the fault information, a fault compensation term is added to the control law to compensate for the adverse effects of actuator faults. Simulation results show that the proposed AFTTCS enables the QUAV to track the desired reference commands in the absence/presence of actuator faults with satisfactory performance.

Fault-Tolerant Model Predictive Control of a Fixed-Wing UAV with Actuator Fault Estimation

The vast majority of today's agtering ayateas poas operational constsinta and have multiple inputa and outputa.This classifen them an Mults-Input Multi-Orutput(MIMO)ayn tena.This pape devekops a novel obeerver-hased fault diagnoas schene with the capability d simultaneoua state and actuator fault estimation for Linear Time-In ariant(LTI)MIMO aystenaa,which is then integrated with Model Predictive Control(MPC)method for achie ving fault-tolerant control.The application within this study is chosen to be the longitudinal flight control o a fixad-wing Unmanmed Aerial Vetücle(UAV).The oberver-based method is dom hüned with two MPC schemas to detect and compansate randomly oeeurring actuator faults in real time.The faults are modeled asa Lans Of Efkctiveess(LOE).For the first(dfident)MPCmethod,a simpke remnniguration can be perkormed in the esent of faulta,as it is based on a abaolute Input foemmlation.Howeve,as the seeond(integrd-action)MPC is based on a incamen tal input formulation,rconfiguration is notrequired,sinee this algorithm has&degrc of implicst fault tokeranee.Numerfcal simulationa danstrate the afetivens of the panposed approach for both MPC sebemes.

变体飞行器传感器故障在线主动容错控制

为保证变体飞行器在传感器故障情况下的稳定飞行性能和良好跟踪效果,提高故障诊断准确度和容错控制能力,针对变体飞行器传感器故障诊断与容错控制问题,提出一种基于考虑属性可靠度的置信规则库(BRB-r)专家系统在线主动容错控制方法。首先,给出变体飞行器的气动参数模型和纵向非线性动力学模型,综合考虑外界扰动和传感器故障,利用最小二乘拟合方法和雅克比线性化方法,建立变体飞行器的切换线性变参数(LPV)故障模型;然后,基于BRB-r专家系统构建变体飞行器传感器故障诊断与容错控制模型,通过统计方法对传感器监测指标进行可靠性分析,并引入证据推理(ER)解析算法,提高故障诊断精度和容错控制效果;最后,利用基于投影算子的协方差矩阵自适应优化策略(P-CMA-ES)算法优化故障诊断与容错控制模型,降低系统的复杂度,提高了故障诊断效率。仿真结果表明,变体飞行器传感器故障诊断精度能够达到98.75%,当传感器故障程度小于50%时,所提方法能够有效克服传感器故障和外界扰动,保证变体飞行器的稳定飞行,具有较强的容错控制能力和鲁棒性能。

基于知识推理的指挥控制软件故障诊断方法

针对当前指挥控制(指控)系统软件缺乏故障诊断方法的问题,将专家系统的构建方法应用于指控软件故障诊断,形成了一套基于知识推理的指控软件故障诊断框架。利用专家系统中完备的缺陷信息知识库,构建了正向推理和深度优先搜索的推理机,从而实现了对指控软件系统的典型故障诊断。最后,通过实例证明,该方法不仅能有效诊断故障原因,还可给出改进建议。

高速铁路电务智能维护中心系统方案研究

结合当前高速铁路电务行车控制设备监测分散且智能化程度不高,难以满足日常维护需要的现状,提出高速铁路电务智能维护中心系统功能需求、基于数据采集层、数据存储层、数据处理层、数据应用层以及可视化展示层的总体架构,构建现场信号机械室、维护中心机房、维护客户端三级的设备布置方案。通过设置独立的厂家维护模块,引入厂家维护数据,解决了不同厂家设备接入中心和数据采集问题,为实现大数据应用奠定了基础。最后以列控改方试验为例,构建了基于故障树的故障诊断专家系统,综合采集数据对智能诊断功能进行了说明。

基于故障树分析的火控系统故障诊断专家系统设计

传统的故障诊断方法应用于火控系统故障诊断时,诊断过程较为复杂,对维修人员有着较高的要求;针对这些局限性,论述了故障树分析法与专家系统之间的关系,提出并设计了基于故障树分析的火控系统故障诊断专家系统;在故障树和数据库的基础上建立知识库和推理机,设计系统软件框架和工作流程,实现对火控系统数据的自动采集、自动存储、自动分析和自动诊断。结论表明该系统能够实现对坦克火控系统的实时监控,对于典型故障可及时准确地诊断并给出可选择的解决方案,为部队提供了简单适用的诊断工具,给今后的装备保障工作带来便利。

一种火控系统故障诊断专家系统

针对故障诊断领域的特点 ,建立了一个用于火控系统故障诊断的专家系统。论述了该系统的知识表示、推理机制和体系结构。实现了将故障监测硬件技术和专家系统软件技术有机结合 ,构造了集硬件、软件为一体的火控系统故障诊断专家系统。

智能诊断技术在水电机组振动故障诊断中的应用

简述了智能诊断技术的发展状况,介绍了智能诊断技术中专家系统、模糊控制、神经网络控制等的特点及在水电机组故障诊断中的应用研究成果,并分析了水电机组振动故障智能诊断技术的发展前景。

矿用空压机远程监控预警及故障诊断专家系统

采用先进的千兆以太环网通讯技术,以可编程序控制器PLC和上位机组态软件为开发平台,对现场检测元件检测的空压机各检测参数进行采集、分析和实时反馈,实现空压机的远程监控和实时预警;并综合运用SQL Server数据库系统和CLIPS专家系统工具建立相应的故障诊断规则,完成矿用空压机远程监控预警及故障诊断专家系统的设计,提高空压机运行的安全系数和对故障的分析能力。

面向对象的水电厂智能故障诊断系统

针对中小型水电厂运行过程中故障诊断的需要，以分布式计算机控制系统的结构为基础，提出一种智能数据采集单元和层次式多专家系统协同作业进行故障诊断的方法，并论述了面向对象的智能化故障诊断系统的体系结构和实施技术。实际运行表明，所提出的方法是有效可行的。

基于神经网络的火控系统故障诊断专家系统

针对某型战机航空火控系统故障诊断方法对维修人员、检测设备依赖性大、故障诊断时间长等弊端,提出将神经网络与专家系统技术相结合应用于该型战机火控系统的故障诊断中。根据火控系统的故障特点给出了其神经网络专家系统的结构,建立了系统知识库,设计了系统运行的主界面和四大运行模块。经部队外场维修人员使用证明,该系统易于维护和使用,故障诊断准确率较高,有较强的鲁棒性。

铝型材生产过程质量控制系统的研究

从模具智能CAD、生产过程在线检测、缺陷诊断专家系统三个方面论述了铝型材生产过程质量控制系统的构成,介绍了各子系统结构及功能。系统具有数据一致性、冗余少、易维护等特点,在实际应用中取得了成功。

基于神经网络推理策略的电梯故障诊断法

针对电梯控制系统中,基于故障树推理法的故障诊断专家系统在线诊断实时性较差,诊断结果准确性偏低的问题,采用基于神经网络推理策略的方法,建立了单故障诊断和复合诊断模型,并给出有权值训练的变步长BP算法。在Matlab环境下,对单故障模型进行了仿真实现,实验结果表明,神经网络推理策略效果优良。