超立方体多处理机系统中基于扩展最优通路矩阵的容错路由

该文在高峰等文章的基础上，提出了针对超立方体结构多处理机系统的扩展最优通路矩阵（Extended Optimal Path Matrices,EOPMs）的概念，并给出了一个建立EIPMs的算法和基于EOPMs的容错路由算法，证明了基于EOPMs的容错路由算法是基于扩展安全向量（ESVs）^[13]和基于最优通路矩阵（OPMs)^[14]容错路由算法的扩展，与原文相比，该算法的存储开销与OPMs,相同，但记录的最优通路的信息，包含了原文所记录的最优通路的信息，使搜索最优通路的能力比它们有进一步的提高。     

Intelligent state estimation for fault tolerant nonlinear predictive control

There is growing realization that on-line model maintenance is the key to realizing long term benefits of a predictive control scheme. In this work, a novel intelligent nonlinear state estimation strategy is proposed, which keeps diagnosing the root cause(s) of the plant model mismatch by isolating the subset of active faults (abrupt changes in parameters/disturbances, biases in sensors/actuators, actuator/sensor failures) and auto-corrects the model on-line so as to accommodate the isolated faults/failures. To carry out the task of fault diagnosis in multivariate nonlinear time varying systems, we propose a nonlinear version of the generalized likelihood ratio (GLR) based fault diagnosis and identification (FDI) scheme (NL-GLR). An active fault tolerant NMPC (FTNMPC) scheme is developed that makes use of the fault/failure location and magnitude estimates generated by NL-GLR to correct the state estimator and prediction model used in NMPC formulation. This facilitates application of the fault tolerant scheme to nonlinear and time varying processes including batch and semi-batch processes. The advantages of the proposed intelligent state estimation and FTNMPC schemes are demonstrated by conducting simulation studies on a benchmark CSTR system, which exhibits input multiplicity and change in the sign of steady state gain, and a fed batch bioreactor, which exhibits strongly nonlinear dynamics. By simulating a regulatory control problem associated with an unstable nonlinear system given by Chen and Allgower [H. Chen, F. Allgower, A quasi infinite horizon nonlinear model predictive control scheme with guaranteed stability, Automatica 34(10) (1998) 1205–1217], we also demonstrate that the proposed intelligent state estimation strategy can be used to maintain asymptotic closed loop stability in the face of abrupt changes in model parameters. Analysis of the simulation results reveals that the proposed approach provides a comprehensive method for treating both faults (biases/drifts in sensors/actuators/model parameters) and failures (sensor/ actuator failures) under the unified framework of fault tolerant nonlinear predictive control.     

基于事件触发的故障诊断与动态调节集成设计

本文发展了一种事件触发采样与更新检测机制、故障诊断及调节的集成设计框架.事件触发技术不仅用于传感器端,同时也用于容错控制器端.所设计的故障诊断观测器能够应用基于事件触发的非均匀采样输出同时估计故障和系统状态,基于所获得的状态和估计信息,构造事件触发更新检测器和动态容错控制器,进而借助于增广系统方法来集成设计两个事件触发检测器、故障诊断观测器和容错控制器,以保证故障系统的性能,同时尽可能的降低传感器、控制器、执行器三者之间的信息传输频率.仿真实例验证了所提方法的可行性和优越性.     

Observer‐based fault diagnosis and self‐restore control for systems with measurement delays

The problems of fault diagnosis and fault‐tolerant control are considered for systems with measurement delays. In contrast to the present fault diagnosis and fault‐tolerant control approaches, which consider only the input delay and/or state delay, the main contribution of this paper consists of proposing a new observer‐based reduced‐order fault diagnoser construction approach and a design approach to dynamic self‐restore fault‐tolerant control law for systems with measurement delays. First, the time‐delay system is transformed into a delay‐free system in form by a special functional‐based delay‐free transformation approach for measurement delays. Then, the fault diagnosis is realized online via the proposed reduced‐order fault diagnoser. Using the results of fault diagnosis, two dynamic self‐restore control laws are designed to make the system isolated from faults. A numerical example demonstrates the feasibility and validity of the proposed scheme. © 2012 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

复杂机载电子系统故障综合诊断技术研究

故障综合诊断技术一直是复杂机载电子系统研发过程中的关键部分,当前的故障诊断技术同时需要机内测试（BIT）和场外自动化测试设备（ATE）的测试结果才能得出诊断结果,诊断效率低,时间长并且不能在线诊断。针对新一代战斗机将更加依赖航空电子系统的趋势,迫切需要一种诊断时间短,且能够实现在线诊断的故障诊断技术。因此,一种基于模型的故障诊断方法被提出。该方法通过融合多信号模型和整数编码故障字典模型,模块间采用多信号模型,单个模块中采用整数编码故障字典模型,克服了多信号模型对测试信息的浪费和整数编码故障字典模型建模困难的缺点,并提出一种多目标测试优选方法,通过优化检测方案,充分发挥BIT的检测性能。该方法通过充分使用BIT的测试信息,摆脱了对场外ATE的依赖,实现了在线快速定位故障并识别故障模式。     

Circuit diagnosis support system for electronics assembly operations

Diagnosis and repair operations are often major bottlenecks in electronics circuit assembly operations. Increasing board density and circuit complexity have made fault diagnosis difficult. But, with shrinking product life cycles and increasing competition, quick diagnosis and feedback is critical for cost control, process improvement, and timely product introduction. This paper describes a case-based diagnosis support system to improve the effectiveness and efficiency of circuit diagnosis in electronics assembly facilities. The system stores individual diagnostic instances rather than general rules and algorithmic procedures, and prioritizes the tests during the sequential testing process. Its knowledge base grows as new faults are detected and diagnosed by the analyzers. The system provides distributed access to multiple users, and incorporates on-line updating features that make it quick to adapt to changing circumstances. Because it is easy to install and update, this method is well-suited for real manufacturing applications. We have implemented a prototype version, and tested the approach in an actual electronics assembly environment. We describe the system's underlying principles, discuss methods to improve diagnostic effectiveness through principled test selection and sequencing, and discuss managerial implications for successful implementation.     

Novel MPC‐Based Fault Tolerant Tracking Control Against Sensor Faults

The problem of active fault‐tolerant tracking control with control input and system output constraints is studied for a class of discrete‐time systems subject to sensor faults. A time‐varying fault‐tolerant observer is first developed to estimate the real system state from the faulty sensor output and control input signals. Then by using the estimated state at each time step, a model predictive control (MPC)‐based fault‐tolerant tracking control scheme is presented to guarantee the desired tracking performance and the given input and output constraints on the faulty system. In comparison with many existing fault‐tolerant MPC methods, its main contribution is that the proposed state estimator is designed by the simple and online numerical computation to tolerate the possible sensor faults, so that the regular MPC algorithm without fault information can be adopted for the online calculation of fault‐tolerant control signal. The potential recursive infeasibility and computational complexity due to the faults are avoided in the scheme. Additionally, the closed‐loop stability of the post‐fault system is discussed. Simulative results of an electric throttle control system verify the effectiveness of the proposed method.     

A nonlinear model predictive control scheme for sensor fault tolerance in observation processes

This article addresses the problem of designing a sensor fault‐tolerant controller for an observation process where a primary, controlled system observes, through a set of measurements, an exogenous system to estimate the state of this system. We consider sensor faults captured by a change in a set of sensor parameters affecting the measurements. Using this parametrization, we present a nonlinear model predictive control (NMPC) scheme to control the observation process and actively detect and estimate possible sensor faults, with adaptive controller reconfiguration to optimize the use of the remaining sensing capabilities. A key feature of the proposed scheme is the design of observability indices for the NMPC stage cost to improve the observability of both the state of the exogenous system and the sensor fault parameters. The effectiveness of the proposed scheme is illustrated through numerical simulations.     

Integrated design of robust fault estimation and fault‐tolerant control against simultaneous actuator and sensor faults

This paper investigates the problems of simultaneous actuator and sensor faults estimation, as well as the fault‐tolerant control scheme for a class of linear continuous‐time systems subject to external disturbances. First, the original system is transformed into a singular form by extending the actuator fault and sensor fault to be parts of the new state. Then, a new estimation technique named non‐fragile proportional‐derivative observer is designed for the singular system to achieve simultaneous estimations of states and faults. With the obtained estimations information, an integrated design of the non‐fragile output feedback fault‐tolerant controller is explored to compensate for the effect of faults by stabilizing the closed‐loop system. Finally, a simulation study on a two‐stage chemical reactor with recycle streams is provided to verify the effectiveness of the proposed approach.     

A model-based approach to robot fault diagnosis

This paper presents a model-based approach to online robotic fault diagnosis: First Priority Diagnostic Engine (FPDE). The first principle of FPDE is that a robot is assumed to work well as long as its key variables are within an acceptable range. FPDE consists of four modules: the bounds generator, interval filter, component-based fault reasoner (core of FPDE) and fault reaction. The bounds generator calculates bounds of robot parameters based on interval computation and manufacturing standards. The interval filter provides characteristic values in each predetermined interval to denote corresponding faults. The core of FPDE carries out a two-stage diagnostic process: first it detects whether a robot is faulty by checking the relevant parameters of its end-effector, if a fault is detected it then narrows down the fault at the component level. FPDE can identify single and multiple faults by the introduction of characteristic values. Fault reaction provides an interface to invoke emergency operation or tolerant control, even possibly system reconfiguration. The paper ends with a presentation of simulation results and discussion of a case study.     

Design of new fault diagnosis and fault tolerant control scheme for non-Gaussian singular stochastic distribution systems

New fault diagnosis (FD) and fault tolerant control (FTC) algorithms for non-Gaussian singular stochastic distribution control (SDC) systems are presented in this paper. Different from general SDC systems, in singular SDC systems, the relationship between the weights and the control input is expressed by a singular state space model, which increases the difficulty in the FD and FTC design. The proposed approach relies on an iterative learning observer (ILO) for fault estimation. The fault may be constant, fast-varying or slow-varying. Based on the estimated fault information, the fault tolerant controller can be designed to make the post-fault probability density function (PDF) still track the given distribution. Simulations are given to show the effectiveness of the proposed FD and FTC algorithms.     

一类非线性系统的故障检测与容错控制算法

针对仿射非线性系统提出了一种稳定的故障检测及容错控制算法.该算法利用神经网络对系统故障进行建模,在线估计故障向量,监测系统运行情况;在反馈回路中引用故障辅助反馈控制回路,实现容错控制;并基于Lyapunov方法进行了稳定性分析.控制系统可运行于两种模式:系统正常时,采用常规反馈控制器(CC);有故障发生时,引入补偿控制来削弱故障影响,保障系统的正常运行.最后对一类非线性电机的仿真控制结果表明了此容错控制方法的有效性.     

Cheap diagnosis using structural modelling and fuzzy-logic-based detection

Practical fault diagnosis can be based on simple, yet efficient, analysis of redundant information about the state of a plant, and diagnostic algorithms can be made without detailed and expensive modelling efforts. This paper shows how it is possible, using structural analysis, to find redundancy relations for linear or non-linear dynamic behaviour, and combine this with fuzzy output observer design to provide an effective diagnostic approach. An adaptive neuro-fuzzy inference method is used. A fuzzy adaptive threshold is employed to cope with practical uncertainty. The methods are demonstrated using measurements on a ship propulsion system subject to simulated faults.     

Active fault‐tolerant consensus control of Lipschitz nonlinear multiagent systems

This article investigates the active fault‐tolerant consensus problem for Lipschitz nonlinear multiagent systems under detailed balanced directed graph and actuator faults. First, a fault detection filter for each agent is designed, and all agents can be divided into two categories: healthy agents and possibly faulty agents. Second, fully distributed adaptive fault‐tolerant consensus protocols for healthy and possibly faulty agents are proposed to achieve state consensus. Third, based on the fault detection method and fault‐tolerant consensus protocols, active fault‐tolerant consensus algorithms are given. Simulation examples are presented to verify the effectiveness of the proposed active fault‐tolerant algorithms.     

一类基于状态估计的非线性系统的智能故障诊断

针对一类含有建模误差的非线性系统,研究了基于状态估计的智能故障诊断方法.首先提出一种状态估计器设计方法;然后在进行状态估计的同时用RBF神经网络来逼近系统所发生的故障.故障估计器的输入为系统的状态估计,所估计出的故障既可用作故障容错控制,也可用作报警.根据微分同胚,将含有建模误差的非线性系统变换为易于分析的规范形式,并在此基础上分析了故障诊断系统的稳定性和鲁棒性.仿真例子证明了该方法的有效性.     

Adaptive neural model-based fault tolerant control for multi-variable processes

An adaptive neural network model-based fault tolerant control approach for unknown non-linear multi-variable dynamic systems is proposed. A multi-layer Perceptron network is used as the process model and is adapted on-line using the extended Kalman filter to learn changes in process dynamics. In this way, the adaptive model will learn the post-fault dynamics caused by actuator or component faults. Then, the inversion of the neural model is used as a controller to maintain the system stability and control performance after fault occurrence. The convergence of the model inversion control is proved using Lyapunov method. The proposed method is applied to the simulation of a two-input two-output continuous-stirred tank reactor to demonstrate the effectiveness of the approach. Several actuator and component faults are simulated on the continuously stirred tank reactor process when the system is under the proposed fault tolerant control. The results have shown a fast recovery of tracking performance and the maintained stability.     

运行控制系统集中式容错控制方法

本文针对运行控制系统,建立了运行优化控制过程的双层结构模型.在此基础上,通过建立相应的自适应故障诊断算法,提出了保证在系统有故障和干扰时仍能渐近优化指标的集中式容错控制方法,利用李雅普诺夫稳定性理论分析了自适应故障诊断算法的构建.已证明:该方法通过调整已优化的设定值来保证在回路控制层出现故障时整个运行控制仍可收敛到其原有的优化控制效果.该方法属于非完备容错控制,仿真结果验证了所提方法的有效性.     

Design of a fault tolerant control system incorporating reliability analysis and dynamic behaviour constraints

In highly automated aerospace and industrial systems where maintenance and repair cannot be carried out immediately, it is crucial to design control systems capable of ensuring desired performance when taking into account the occurrence of faults/failures on a plant/process; such a control technique is referred to as fault tolerant control (FTC). The control system processing such fault tolerance capability is referred to as a fault tolerant control system (FTCS). The objective of FTC is to maintain system stability and current performance of the system close to the desired performance in the presence of system component and/or instrument faults; in certain circumstances a reduced performance may be acceptable. Various control design methods have been developed in the literature with the target to modify or accommodate baseline controllers which were originally designed for systems operating under fault-free conditions. The main objective of this article is to develop a novel FTCS design method, which incorporates both reliability and dynamic performance of the faulty system in the design of a FTCS. Once a fault has been detected and isolated, the reconfiguration strategy proposed in this article will find possible structures of the faulty system that best preserve pre-specified performances based on on-line calculated system reliability and associated costs. The new reconfigured controller gains will also be synthesised and finally the optimal structure that has the ‘best’ control performance with the highest reliability will be chosen for control reconfiguration. The effectiveness of this work is illustrated by a heating system benchmark used in a European project entitled intelligent Fault Tolerant Control in Integrated Systems (IFATIS EU-IST-2001-32122).     

Fault tolerant control for joint structure in PEMS high speed maglev train

The PEMS high speed maglev train, which features a permanent magnet inside an electromagnet, is a new kind of maglev train for long distance intercity transportation. The joint structure, which consists of two single levitation sub‐systems, is the fundamental levitation unit. Two kinds of faults are considered and corresponding fault tolerant control strategies are proposed. The first fault condition is when a gap sensor that is part of a single levitation system is faulty. For this kind of fault, a fault tolerant control strategy based on signal reconfiguration is proposed. The second fault condition is when the whole of a single levitation sub‐system is faulty. Under this condition, a faulty model is firstly established, then a fault tolerant control strategy is designed. When this kind of fault is detected, a switch from the normal controller to the fault tolerant controller can make the faulty system stable.