测量丢失概率不确定的网络化系统的鲁棒故障检测

研究一类具有测量数据丢失概率不确定的网络化系统的鲁棒故障检测问题,系统用概率属于一个区间的Bernoulli随机二进制切换序列来描述测量数据丢失.设计一个基于观测器的鲁棒故障检测滤波器(RFDF),对于区间内的每一个概率,RFDF残差误差输出对故障敏感且对具有L2有界的未知干扰输入有一定的鲁棒性,应用线性矩阵不等式方法,给出并证明了此RFDF的存在条件.最后通过例子说明了该方法的有效性.

     

存在多路数据丢失的线性离散时变系统故障检测滤波器设计

本文研究一类存在多路测量数据丢失的线性离散时变系统故障检测滤波器设计问题,系统的数据丢失现象由一族在给定区间范围内取值的相互无关的随机变量描述.采用基于观测器的鲁棒Hx故障检测滤波器作为残差产生器,通过引入新的随机变量,将故障检测滤波器的设计问题转化为一类具有乘性噪声影响的随机时变系统有限时间域内的Hx滤波问题运用Ly...     

具有时变采样周期的网络化控制系统故障检测

针对具有时变采样周期和时延的网络化控制系统(NCS)故障检测问题,通过矩阵 Jordan 变换,将时变采样周期与时延的不确定霆转化为NCS系统结构参数的不确定霆,建立离散时间凸多面体不确定系统模雿。设计鲁棒故障检测滤波器(RFDF)作为残差发生器,将故障检测问题转化为RFDF的设计问题,通过陑霆矩阵不等式给出滤波器存在的充分条件。数值仿真结果表明,所设计的RFDF滤波器能较快复现故障雷号,对外部干扰和不确定的采样周期及时延具有鲁棒霆。     

具有测量数据丢失的网络化系统的故障检测滤波

研究一类具有测量数据部分丢失的网络化系统的故障检测滤波器设计问题. 测量数据的丢失假设满足已知概率的Bernoulli分布. 设计一个故障检测滤波器, 使残差误差系统均方指数稳定且具有一定的扰动衰减水平. 采用线性矩阵不等式方法, 给出了故障检测滤波器存在的充分条件. 最后通过例子说明该方法的有效性.     

测量数据丢失的随机不确定系统鲁棒滤波递推算法

针对一类具有测量数据丢失的不确定离散随机系统,研究了鲁棒状态估计问题,基于间断观测滤波算法和规则最小二乘优化理论,给出一种Kalman形式的递推滤波算法.对于测量数据丢失的问题,采用已知概率的Bernoulli随机序列,使得对于所有可能的测量数据丢失和所能容许的不确定性,间断观测鲁棒状态估计递推算法是稳定的.最后,通过数值仿真和对比结果验证了所提出算法的可行性.     

存在多个数据包丢失的网络化系统的故障检测

研究一类存在多个数据包丢失的网络化不确定系统的鲁棒故障检测问题。不确定对象为凸多面体离散时间模型。多个数据丢失现象由具有一般概率密度的随机变量描述。利用随机系统的Lyapunov稳定性理论和参数依赖方法给出了使残差信号与加权故障信号之间的误差尽可能小的鲁棒故障检测滤波器的存在性条件。借助于线性矩阵不等式组的可行解得到了故障检测滤波器增益。仿真例子表明了所给方法的有效性。     

基于鲁棒正不变集的传感器故障区间估计

针对具有传感器故障和未知扰动与测量噪声的线性离散系统, 提出了一种传感器故障区间估计方法. 将传感器故障视为增广状态, 原始系统转化为一个等效的广义系统. 为了得到故障的点估计同时抑制扰动和噪声的影响, 基于有界实引理设计了一个针对广义系统的鲁棒状态观测器. 然后, 通过中心对称多胞体技术实现对故障的区间估计并基于鲁棒正不变集给出了一种降低区间估计计算量的方法. 最后, 通过一个垂直起降(Vertical take-off and landing, VTOL)飞行器线性化模型的仿真算例验证了所提出方法的有效性与优越性.     

基于混杂系统方法的一类采样数据系统鲁棒故障检测

针对具有连续时间过程噪声和离散时间测量噪声的采样数据系统, 提出了一种新的鲁棒故障检测直接设计方法. 首先利用具有有限跳变的线性系统作为残差产生器, 采样数据系统的鲁棒故障检测设计问题被描述成采样数据滤波问题, 然后给出有限跳变线性系统有界实引理的线性矩阵不等式(LMI)表达形式, 基于此, 推导出采样数据系统鲁棒故障检测滤波器的存在条件及设计参数, 并将所提方法推广到具有结构不确定性的采样数据系统上. 所设计的滤波器能够保证残差与故障之间误差最小, 并对过程噪声、测量噪声、结构不确定性等因素鲁棒. 最后, 通过数值仿真对所提方法的可行性进行了验证.     

基于T-S 模糊模型的一类非线性网络控制系统故障检测

针对同时存在网络时延和数据包丢失的网络环境,研究了一类非线性网络控制系统的鲁棒故障检测问 题．基于不确定T-S 模糊模型描述的非线性网络控制系统模型,完成了网络环境下鲁棒故障检测观测器的设计,使 得残差信号对故障敏感而对外部扰动具有鲁棒性．构造Lyapunov-Krasovskii 函数,并引入一个积分不等式,给出了 使得观测器误差动态系统渐近稳定的充分条件．采用线性矩阵不等式技术将鲁棒故障检测问题转化为具有线性矩阵 不等式约束的凸优化问题求解．仿真算例验证了上述方法应用于此类系统的故障检测的有效性．     

一类线性Markov 跳跃区间时滞系统的 鲁棒??∞ 故障检测滤波器设计

研究一类线性Markov跳跃区间时滞系统的鲁棒H∞故障检测滤波器设计问题.采用基于自适应观测器的故障检测滤波器作为残差产生器,将鲁棒H∞故障检测滤波器设计问题归结为随机H∞滤波问题.应用Lyapunov-Krasovskii方法,通过引入松弛矩阵推导证明了问题可解的时滞依赖充分条件,并进一步通过求解线性矩阵不等式给出了故障检测滤波器参数矩阵的解.仿真算例验证了所提出方法的有效性.     

Detection of intermittent faults for nonuniformly sampled multi-rate systems with dynamic quantisation and missing measurements

ABSTRACT

This paper is concerned with the fault detection problem for a class of networked multi-rate systems with nonuniform sampling and dynamic quantization. The sampling interval of the measurements is allowed to be nonuniform that is governed by a time-homogenous Markov process with partly unknown and uncertain transition probabilities. The measured output is quantized by a dynamic quantizer and then transmitted through communication network subject to data missing. The main purpose of the problem under consideration is to design sampling-interval-dependent fault detection filters such that, in the simultaneous presence of nonuniform sampling, dynamic quantization, intermittent faults as well as missing measurements, the robustness of residuals with respect to the disturbance and the sensitivity of the residuals against the fault are guaranteed. Finally, a three-tank system is utilized to illustrate the effectiveness of the proposed fault detection scheme.     

Robust fault detection for networked systems with communication delay and data missing

In this paper, the robust fault detection problem is investigated for a class of discrete-time networked systems with unknown input and multiple state delays. A novel measurement model is utilized to represent both the random measurement delays and the stochastic data missing phenomenon, which typically result from the limited capacity of the communication networks. The network status is assumed to vary in a Markovian fashion and its transition probability matrix is uncertain but resides in a known convex set of a polytopic type. The main purpose of this paper is to design a robust fault detection filter such that, for all unknown inputs, possible parameter uncertainties and incomplete measurements, the error between the residual signal and the fault signal is made as small as possible. By casting the addressed robust fault detection problem into an auxiliary robust H_∞ filtering problem of a certain Markovian jumping system, a sufficient condition for the existence of the desired robust fault detection filter is established in terms of linear matrix inequalities. A numerical example is provided to illustrate the effectiveness and applicability of the proposed technique.     

Robust fault detection for Markovian jump systems with unreliable communication links

This article addresses the problem of robust fault detection for Markovian jump linear systems with unreliable communication links. In the network communication channel, the effects of signal quantisation and measurement missing, which appears typically in a network environment, are taken into consideration simultaneously. A stochastic variable satisfying the Bernoulli random binary distribution is utilised to model the phenomenon of the measurements missing. The aim is to design a fault detection filter such that, for all unknown input and incomplete measurements, the error between the residual and weighted faults is made as small as possible. A sufficient condition for the existence of the desired fault detection filter is established in terms of a set of linear matrix inequalities. A simulation example is provided to illustrate the effectiveness and applicability of the proposed techniques.     

Robust fault detection with missing measurements

This paper investigates the problem of robust fault detection for uncertain systems with missing measurements. The parameter uncertainty is assumed to be of polytopic type, and the measurement missing phenomenon, which appears typically in a network environment, is modelled by a stochastic variable satisfying the Bernoulli random binary distribution. The focus is on the design of a robust fault detection filter, or a residual generation system, which is stochastically stable and satisfies a prescribed disturbance attenuation level. This problem is solved in the parameter-dependent framework, which is much less conservative than the quadratic approach. Both full-order and reduced-order designs are considered, and formulated via linear matrix inequality (LMI) based convex optimization problems, which can be efficiently solved via standard numerical software. A continuous-stirred tank reactor (CSTR) system is utilized to illustrate the design procedures.     

基于观测器的多智能体系统一致性控制与故障检测

针对一类受到未知干扰的非线性多智能体系统,提出了一种鲁棒一致性控制与故障检测算法.首先,针对每个智能体系统设计了一个未知输入非线性观测器.然后,基于观测器的状态估计信息,设计了鲁棒一致性控制协议.控制协议保证了给定的干扰抑制性能指标.接着,考虑智能体出现故障的情形,采用自适应阈值法,提出了一种分布式故障检测算法.最后,以多个直流电机驱动的单摆系统为例进行了仿真实验,仿真结果表明了一致性控制与故障检测算法的有效性.     

Fault Detection for A Class of Closed-loop Hypersonic Vehicle System via Hypothesis Test Method

This paper studies the fault detection problem for a class of hypersonic vehicle with actuator faults, disturbances and random noises. To handle the unknown disturbances, an unknown input Kalman filter (UIKF) is presented to estimate the unknown system states and disturbances, simultaneously. Considering that the closed-loop structure brings the robustness to the hypersonic vehicle, which could cover some faults, the Total Measurable Fault Information Residual (ToMFIR) is employed as the fault detection residual. Moreover, to deal with the random noises, the hypothesis testing method is utilized to obtain the thresholds under some fault detection performances (false alarm rate and missing alarm rate). The fault detectability condition is also derived. Finally, the simulations verify the effectiveness of the proposed fault detection method.

     

Quadrotor Sensor Fault Diagnosis with Experimental Results

This paper presents a fault detection, isolation, and estimation scheme for sensor bias faults in accelerometer and gyroscope measurements of quadrotor unmanned air vehicles (UAVs). Based on sliding-mode observer techniques, a robust estimation of the quadrotor roll and pitch angles is obtained by using only accelerometer measurements. Then, a diagnostic scheme is developed for detecting, isolating, and estimating sensor bias faults in the gyroscope and accelerometer measurements. Structured residuals are generated, allowing the detection and isolation of multiple simultaneous sensor faults under consideration. After the faults are detected and isolated, two nonlinear estimators are employed to provide an estimate of the unknown fault magnitude. The stability and estimation performance properties of the nonlinear estimators are established. The sensor fault diagnosis algorithm is implemented and evaluated through experimental results using a real-time indoor quadrotor test environment.     

采样数据系统故障检测的H∞方法

提出一种对采样数据系统进行故障检测的H_∞方法. 首先构造离散时间故障检测系统, 分析残差产生器的动态特性. 然后从故障检测的角度引入算子, 定量考察连续时间未知输入信号和故障信号对离散时间残差信号的影响. 最后优化残差产生器的参数, 使得故障检测系统对未知输入具有较强的鲁棒性, 同时对故障具有较高的灵敏度.     

基于未知输入观测器的非线性广义系统执行器故障检测和重构

针对一类含有未知扰动广义非线性系统的执行器故障,本文提出一种重构算法。首先设计未知输入观测器对干扰鲁棒,作为故障检测观测器。检测到发生故障后,通过提出含有误差比例项和积分项的故障估计算法,形成自适应观测器,实现准确快速地估计故障,同时估计状态变量。根据李雅普诺夫稳定理论给出估计误差一致最终有界的充分条件。最后仿真验证该类观测器和重构算法的有效性。