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.     

存在未知时延和Markov 丢包的网络控制系统故障检测与优化

将网络控制系统(NCSs) 的未知短时延处理成范数有界不确定性, 结合Markov 丢包影响将NCSs 建模为不确定Markov 跳变系统, 设计模态依赖的鲁棒故障检测滤波器. 为了提高检测系统性能, 采用后置滤波器对残差信号进行时域优化, 并以Moore-Penrose 逆形式给出其最优解. 同时, 设计自适应检测阈值, 并给出时变参数阵的迭代方法,降低了计算量. 数值仿真表明, 所提出的方法能够有效地抑制时延和丢包影响, 提高故障检测系统的检测能力和检测速度.

     

部分拓扑切换概率未知的移动传感网保性能一致性控制研究

本文研究了基于马尔科夫切换拓扑的移动传感网保性能一致性问题.网络拓扑切换由一般的马尔科夫链驱动,其初始和转移概率部分未知.切换拓扑集中的每个拓扑皆是带有树的有向拓扑图.借助定义包括接收、发送信息和控制输入的新的全局能耗函数,可以得到切换分布式一致性控制器集合.然后经过状态变换,一致性控制问题转化为减阶的马尔科夫跳跃系统的保性能问题.通过分析马尔科夫跳跃系统的稳定性,提出了可以同时计算次优的一致性控制器增益和次小能耗上界的算法.最后,通过数值仿真检验了控制器设计方法的性能.     

Fault detection for discrete-time networked nonlinear systems with incomplete measurements

This article addresses the problem of fault detection (FD) for discrete-time networked systems with global Lipschitz nonlinearities and incomplete measurements, including time delays, packet dropouts and signal quantisation. By utilising a discrete-time homogeneous Markov chain, an improved model which considers packet dropout compensation has been proposed to describe the above network-induced phenomena. We aim to design a mode-dependent fault detection filter (FDF) such that the FD system is asymptotically mean-square stable and satisfies a prescribed attenuation level. The addressed FD problem is then converted into an auxiliary H _∞ filtering problem of Markov jump system with time-varying delay. A sufficient condition for the existence of the FDF is derived in terms of certain linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of the desired FDF can also be characterised. A numerical example is exploited to show the effectiveness of the results obtained.     

Fault detection for a class of nonlinear stochastic systems with Markovian switching and mixed time-delays

This article is concerned with the fault detection (FD) problem for a class of nonlinear stochastic systems with Markovian switching and mixed time-delays. The stochastic system under consideration contains discrete and distributed mode-dependent delays, nonlinearities as well as Markovian switching. Considering a new sensor fault model, which can express the failures of the loss of effectiveness and the outage, a novel FD scheme is proposed such that it is valid for this class of sensor faults. In addition, delay-dependent conditions, which include some existing results, that capture the sensitivity performance and attenuation performance are derived. Then the FD filter gains are characterised in terms of the solutions to a convex optimisation problem. Finally, an aircraft application is given to demonstrate the effectiveness of the proposed method.     

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.     

Necessary and sufficient conditions for mean square consensus under Markov switching topologies

This article deals with the mean square consensus problem for second-order discrete-time multi-agent systems. Both cases of systems with and without time delays in Markov switching topologies are considered. With the introduced control protocols, necessary and sufficient conditions for mean square consensus of second-order multi-agent systems are derived. Under the given control protocols in Markov switching topologies, the second-order multi-agent systems can reach mean square consensus if and only if each union of the graphs corresponding to all the nodes in closed sets has a spanning tree. Finally, a simulation example is provided to illustrate the effectiveness of our theoretical results.     

Robust fault detection for discrete-time Markovian jump systems with mode-dependent time-delays

This paper investigates a fault detection problem for a class of discrete-time Markovian jump systems with norm-bounded uncertainties and mode-dependent time-delays. Attention is focused on constructing the residual generator based on the filter which its parameters matrices are dependent on the system mode, that is, the fault detection filter is a Markovian jump system as well. The design of fault detection filter is reduced to H-infinity filtering problem by using H-infinity control theory, which can guarantee the difference between the residual and the fault (or, more generally weighted fault) as small as possible in the context of enhancing the robustness of residual to modeling errors, control inputs and unknown inputs. Sufficient condition for the existence of the above filters is established by means of linear matrix inequalities, which can be readily {solved by using standard numerical software. A numerical example is given to illustrate the feasibility of the proposed method.     

Robust fault detection for discrete-time Markovian jump systems with mode-dependent time-delays

This paper investigates a fault detection problem for a class of discrete-time Markovian jump systems with norm-bounded uncertainties and mode-dependent time-delays. Attention is focused on constructing the residual generator based on the filter of which its parameters matrices are dependent on the system mode, that is, the fault detection filter is a Markovian jump system as well. The design of fault detection filter is reduced to H-infinity filtering problem by using H-infinity control theory, which can guarantee the difference between the residual and the fault (or, more generally weighted fault) as small as possible in the context of enhancing the robustness of residual to modeling errors, control inputs and unknown inputs. Sufficient condition for the existence of the above filters is established by means of linear matrix inequalities, which can be readily solved by using standard numerical software. A numerical example is given to illustrate the feasibility of the proposed method.     

Fault detection for a class of networked nonlinear systems subject to imperfect measurements

This paper addresses the problem of fault detection (FD) for discrete-time networked systems with global Lipschitz conditions and imperfect measurements. By using Bernoulli stochastic variables and a switching signal, a unified model is proposed to describe four kinds of imperfect measurements, that is, access constraints, time delays, packet dropouts, and signal quantization. We aim to design a fault detection filter (FDF) such that, for all external disturbances and imperfect measurements, the error between the residual and fault is made as small as possible. The addressed FD problem is then converted into an auxiliary H _∞ filtering problem for discrete-time stochastic switched systems with multiple time-varying delays. By applying Lyapunov-Krasovskii approach, a sufficient condition for the existence of the FDF is derived in terms of certain linear matrix inequalities (LMIs). When these LMIs are feasible, the explicit expression of the desired FDF can also be characterized. A numerical example is exploited to show the effectiveness of the results obtained.     

Event-triggered fault detection for discrete-time Markovian jump systems in finite frequency domain

This paper is concerned with the design of the finite frequency fault detection (FD) filter based on the event-triggered scheme (ETS) for discrete-time Markovian jump (DMJ) systems with Lipschitz functions, time-varying delays, and packet dropouts. A novel FD filter subject to ETS and data missing is developed, and the augmented filter system is rewritten as a DMJ-linear parameter varying (DMJ-LPV) system through a reformulated Lipschitz property. Then, two novel lemmas are proposed to guarantee the DMJ-LPV system robust to unknown disturbances and sensitive to finite frequency faults. Next, the proposed lemmas are deduced into linear matrix inequalities by using Finsler's lemma and S-procedure. Finally, the application of Chua's circuit system is employed to illustrate the validity and superiority of the proposed theory.     

Distributed state estimation for uncertain Markov‐type sensor networks with mode‐dependent distributed delays

In this paper, the distributed state estimation problem is investigated for a class of sensor networks described by uncertain discrete‐time dynamical systems with Markovian jumping parameters and distributed time‐delays. The sensor network consists of sensor nodes characterized by a directed graph with a nonnegative adjacency matrix that specifies the interconnection topology (or the distribution in the space) of the network. Both the parameters of the target plant and the sensor measurements are subject to the switches from one mode to another at different times according to a Markov chain. The parameter uncertainties are norm‐bounded that enter into both the plant system as well as the network outputs. Furthermore, the distributed time‐delays are considered, which are also dependent on the Markovian jumping mode. Through the measurements from a small fraction of the sensors, this paper aims to design state estimators that allow the nodes of the sensor network to track the states of the plant in a distributed way. It is verified that such state estimators do exist if a set of matrix inequalities is solvable. A numerical example is provided to demonstrate the effectiveness of the designed distributed state estimators. Copyright © 2011 John Wiley & Sons, Ltd.     

网络化切换控制系统故障检测与优化设计

研究存在未知短时延、丢包和系统不确定性的网络化切换控制系统故障检测与时域优化问题. 首先基 于观测器构建残差发生器, 结合Lyapunov 函数方法和平均驻留时间方法分析系统的稳定性, 并以线性矩阵不等式(LMI) 形式给出故障检测滤波器的求解方法; 然后为了改善故障检测系统的性能, 采用后置滤波器对残差信号进行时域优化, 并利用奇偶空间方法给出其最优解; 最后设计并推导出自适应阈值. 仿真结果验证了所提出方法的有效性.

     

Reduced-order filtering for networks with Markovian jumping parameters and missing measurements

The problem of reduced-order H _∞ filters design for Markovian jumping complex networks with polytopic time-varying transition probability matrices is first addressed in this paper, where the dynamic of each node is described by the sector-bounded nonlinearity. For the measurements, both quantisation and packet dropouts are considered, where each node has its own packet dropout rate. By using the mode- and transition probability-dependent Lyapunov function approach, two sufficient conditions are provided to ensure the stochastic stability and the disturbance attenuation performance of the resulting filtering error system. Then, the mode-independent reduced-order filters design method is proposed, and the filter parameters are given explicitly by linear matrix inequality method. Finally, the effectiveness of the theoretic results presented is illustrated via a numerical example which contains performance comparison of different mode-independent reduced-order filters.     

Robust fuzzy control for uncertain discrete-time nonlinear Markovian jump systems without mode observations

This paper studies the robust fuzzy control problem of uncertain discrete-time nonlinear Markovian jump systems without mode observations. The Takagi and Sugeno (T-S) fuzzy model is employed to represent a discrete-time nonlinear system with norm-bounded parameter uncertainties and Markovian jump parameters. As a result, an uncertain Markovian jump fuzzy system (MJFS) is obtained. A stochastic fuzzy Lyapunov function (FLF) is employed to analyze the robust stability of the uncertain MJFS, which not only is dependent on the operation modes of the system, but also directly includes the membership functions. Then, based on this stochastic FLF and a non-parallel distributed compensation (non-PDC) scheme, a mode-independent state-feedback control design is developed to guarantee that the closed-loop MJFS is stochastically stable for all admissible parameter uncertainties. The proposed sufficient conditions for the robust stability and mode-independent robust stabilization are formulated as a set of coupled linear matrix inequalities (LMIs), which can be solved efficiently by using existing LMI optimization techniques. Finally, it is also demonstrated, via a simulation example, that the proposed design method is effective.     

Robust stability of Markovian jump discrete-time neural networks with partly unknown transition probabilities and mixed mode-dependent delays

This article discusses the robust stability problem for a class of uncertain Markovian jump discrete-time neural networks with partly unknown transition probabilities and mixed mode-dependent time delays. The transition probabilities of the mode jumps are considered to be partly unknown, which relax the traditional assumption in Markovian jump systems that all of them must be completely known a priori. The mixed time delays consist of both discrete and distributed delays that are dependent on the Markovian jump modes. By employing the Lyapunov functional and linear matrix inequality approach, some sufficient criteria are derived for the robust stability of the underlying systems. A numerical example is exploited to illustrate the developed theory.     

转移概率未知下具有双Markov 链的网络控制系统控制器设计

研究一类基于Markov模型的网络控制系统的稳定性和镇定控制器设计问题.针对网络控制系统中受控对象模型的随机切换和通信过程中的丢包问题,利用具有两个独立Markov链的离散时间Markov跳跃系统进行建模.在该Markov跳跃系统模态转移概率矩阵部分元素未知的情况下,充分考虑转移概率的约束条件,给出系统可镇定的充要条件和状态反馈控制器的设计方法.最后通过仿真示例验证了所提出方法的有效性.     

非齐次马尔可夫跳跃正线性系统的稳定与镇定

本文研究一类非齐次马尔可夫跳跃正线性系统的稳定与镇定问题.该系统中模态的变化服从非齐次马尔可夫过程,其模态转移速率/概率矩阵是随时间随机变化的,且变化规律由一个高层马尔可夫过程描述,本文提出一种双层马尔可夫跳跃正系统模型来刻画此类系统特征.在此基础上,利用切换线性余正李雅普诺夫函数给出此类连续和离散时间非齐次马尔可夫跳跃正线性系统平均稳定的判据.然后,运用线性规划方法设计依赖于模态–模态转移速率/概率矩阵的状态反馈控制器,进而实现闭环系统的平均稳定性.最后,以功率分配系统为例给出仿真算例,验证了所设计控制策略的有效性.     

A Reduced-order Fault Detection Filter Design for Polytopic Uncertain Continuous-time Markovian Jump Systems with Time-varying Delays

In this article, the fault detection (FD) reduced-order filtering problem is investigated for a family of polytopic uncertain continuous-time Markovian jump linear systems (MJLSs) with time-varying delays. Under meeting the the premise of fault detection accuracy, the reduced order fault detection filters are desirable in applications where fast data processing and saving computing space are necessary. Then, by the aid of the Markovian Lyapunov-Krasovskii functional and convex polyhedron techniques, some novel time-varying delays and polytopic uncertain sufficient conditions are proposed to insure the existence of the FD reduced-order filter. Finally, a simulated continuous stirred tank reactor process example is provided to verify the feasibility of the proposed methodology.     

Simultaneous fault detection and control for switched systems with actuator faults

This paper is concerned with the fault detection and control problem for discrete-time switched systems. The actuator faults, especially ‘outage cases’, are considered. The detector/controller is designed simultaneously such that the closed-loop system switches under an average dwell time, and when a fault is detected, an alarm is generated and then the controller is switched to allow the norm of the states of the subsystem to increase within the acceptable limits. Thus, a switching strategy which combines average dwell time switching with event-driven switching is proposed. Under this switching strategy, the attention is focused on designing the detector/controller such that estimation errors between residual signals and faults are minimised for the fulfillment of fault detection objectives; simultaneously, the closed-loop system becomes asymptotically stable for the fulfillment of control objectives. A two-step procedure is adopted to obtain the solutions through satisfying a set of linear matrix inequalities. An example comprising of three cases is considered. Through these cases, it is demonstrated that the fault detection and control for switched systems using a two-stage switching strategy and asynchronous switching are feasible.