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...     

一类时滞LPV 系统的鲁棒故障检测

研究一类具有参数依赖时滞的线性参数变化系统的鲁棒故障检测问题，使残差信号和故障信号之问的误差最小，同时提高残差信号对控制输入和未知输入信号的鲁棒性．基于依赖于时变参数的滤波器构造残差产生系统，利用H∞控制理论将故障检测滤波器的设计归结为H∞滤波问题，应用线性矩阵不等式技术得到了此类系统鲁棒故障检测滤波器存在的充分条件．数值仿真表明所提方法是可行的．     

一种鲁棒故障检测与反馈控制的最优集成设计方法

研究线性不确定系统的反馈控制器与鲁棒故障检测滤波器集成设计问题.基于新提出 的性能指标函数,将鲁棒故障检测滤波器设计问题归结为最优化问题,通过求解Riccati方程可 得到鲁棒故障检测滤波器设计问题的最优解.在共用同一状态观测器的情况下,将反馈控制器 和鲁棒故障检测滤波器的集成设计问题归结为两目标优化问题,解决了同时满足闭环控制系统 设计要求和故障诊断系统鲁棒性能的最优集成设计问题.简例验证了提出算法的有效性.     

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．     

具有随机丢包的非线性网络化控制系统鲁棒故障检测

针对具有随机丢包的Lipschitz非线性网络化控制系统,研究了系统存在外部干扰情况下的鲁棒故障检测问题。由于带宽有限,传感器-控制器和控制器-执行器的网络通道中存在随机数据包丢失,鉴于此,设计一种基于观测器的故障检测滤波器,给出存在故障检测滤波器的充分条件,使误差系统均方指数稳定并达到鲁棒H∞干扰抑制水平,同时给出基于观测残差均方值的故障检测策略。通过仿真算例验证了所提出方法的有效性。     

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.

     

基于依参数分离算子的鲁棒可靠滤波器设计

针对凸面体不确定系统并考虑传感器发生故障的情况, 基于二次型分离算子进行了鲁棒可靠滤波器设计的研究. 利用不确定系统鲁棒镇定时的拓扑解释, 采用分离算子将不含故障描述的系统矩阵与故障描述矩阵进行解耦, 从而获得对故障不敏感的鲁棒可靠滤波器. 为进一步降低设计的保守性, 文中还给出了一种依参数分离算子的滤波器存在条件, 并将滤波器设计转化为线性矩阵不等式 (LMIs) 表述的凸优化问题. 仿真实例验证了文中所提出设计方法的有效性.     

带丢失观测和不确定噪声方差系统改进的鲁棒协方差交叉融合稳态Kalman滤波器

对带丢失观测和不确定噪声方差的线性定常多传感器系统,引入虚拟噪声将原系统转化为仅带不确定噪声方差的系统.根据极大极小鲁棒估值原理,用Lyapunov方程方法提出局部鲁棒稳态Kalman滤波器及其实际方差最小上界,并利用保守的局部滤波误差互协方差,提出一种改进的鲁棒协方差交叉(covariance intersection,CI)融合稳态Kalman滤波器及其实际方差最小上界.证明了所提出的鲁棒局部和融合滤波器的鲁棒性,并证明了改进的CI融合器鲁棒精度高于原始CI融合鲁棒精度,且高于每个局部滤波器的鲁棒精度.一个仿真例子验证所提出结果的正确性和有效性.     

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。     

Fuzzy-model-based robust fault detection with stochastic mixed time delays and successive packet dropouts

This paper is concerned with the network-based robust fault detection problem for a class of uncertain discrete-time Takagi-Sugeno fuzzy systems with stochastic mixed time delays and successive packet dropouts. The mixed time delays comprise both the multiple discrete time delays and the infinite distributed delays. A sequence of stochastic variables is introduced to govern the random occurrences of the discrete time delays, distributed time delays, and successive packet dropouts, where all the stochastic variables are mutually independent but obey the Bernoulli distribution. The main purpose of this paper is to design a fuzzy fault detection filter such that the overall fault detection dynamics is exponentially stable in the mean square and, at the same time, the error between the residual signal and the fault signal is made as small as possible. Sufficient conditions are first established via intensive stochastic analysis for the existence of the desired fuzzy fault detection filters, and then, the corresponding solvability conditions for the desired filter gains are established. In addition, the optimal performance index for the addressed robust fuzzy fault detection problem is obtained by solving an auxiliary convex optimization problem. An illustrative example is provided to show the usefulness and effectiveness of the proposed design method.     

多模态It随机系统的均方稳定性与鲁棒镇定

研究由连续时间Markov链所确定的多模态It^o随机系统的均方稳定性与鲁棒镇定 ,得到了一般多模态It^o随机系统的k阶矩指数稳定性定理 ,线性不确定系统的均方稳定性定理 ,给出了线性不确定系统的鲁棒镇定控制器 .     

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 and isolation in stochastic systems

This article outlines the formulation of a robust fault detection and isolation (FDI) scheme that can precisely detect and isolate simultaneous actuator and sensor faults for uncertain linear stochastic systems. The given robust fault detection scheme based on the discontinuous robust observer approach would be able to distinguish between model uncertainties and actuator failures and therefore eliminate the problem of false alarms. Since the proposed approach involves estimating sensor faults, it can also be used for sensor fault identification and the reconstruction of true outputs from faulty sensor outputs. Simulation results presented here validate the effectiveness of the proposed robust FDI system.     

Simultaneous Fault Detection and Control for Markovian Jump Systems with General Uncertain Transition Rates

This paper investigates the simultaneous control and fault detection of Markovian jump systems with general transition rates allowed to be unknown and known with uncertainties. By introducing slack matrices, a new approach is developed to conquer the nonlinearity induced by unknown and uncertain transition rates. Then, sufficient conditions are presented to ensure the stochastic stability of the resultant closed-loop system and meet the robust and detection performance indices. Finally, an example is given to illustrate the effectiveness of the proposed theoretical results.     

Robust detection of intermittent multiplicative sensor fault

In this paper, the detection problem of intermittent multiplicative sensor fault is investigated for stochastic uncertain systems. A robust optimal filter is designed according to the criterion of minimum estimation error covariance. Then, based on this, a residual generator is constructed, and the quantitative effect of the fault on it is discussed in detail. After that we design the evaluation function and detection threshold to achieve intermittent fault detection. Our proposed strategy has a recursive form and only includes simple arithmetic operations, thus it is suitable for real‐time online applications. Finally, a simulation example is given to demonstrate the effectiveness of the proposed strategy.     

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.     

An LMI approach to design robust fault detection filter for uncertain LTI systems

In this paper, the robust fault detection filter design problem for uncertain linear time-invariant (LTI) systems with both unknown inputs and modelling errors is studied. The basic idea of our study is to use an optimal residual generator (assuming no modelling errors) as the reference residual model of the robust fault detection filter design for uncertain LTI systems with modelling errors and, based on it, to formulate the robust fault detection filter design as an H_∞ model-matching problem. By using some recent results of H_∞ optimization, a solution of the optimization problem is then presented via a linear matrix inequality (LMI) formulation. The main results include the development of an optimal reference residual model, the formulation of robust fault detection filter design problem, the derivation of a sufficient condition for the existence of a robust fault detection filter and a construction of it based on the LMI solution parameters, the determination of adaptive threshold for fault detection. An illustrative design example is employed to demonstrate the effectiveness of the proposed approach.     

An ILMI Approach to RFDF for Uncertain Linear Systems with Nonlinear Perturbations

The robust fault detection filter design for uncertain linear systems with nonlinear perturbations is formulated as a two-objective optimization problem. Solvable conditions for the existence of such a robust fault detection filter are given in terms of matrix inequalities (MIs), which can be solved by applying iterative linear matrix inequality (ILMI) techniques. Particularly, compared with two existing LMI methods, the developed algorithm is more generalized and less conservative. An illustrative example is given to show the effectiveness of the proposed method.