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distributed H_∞ filtering for a Class of Discrete-Time Markov Jump Lur'e Systems With Redundant Channels

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2016年第3期63卷 1876-1885页

作者： Zhu, Yanzheng Zhang, Lixian Zheng, Wei Xing Harbin Inst Technol Sch Astronaut Harbin 150080 Peoples R China Univ Western Sydney Sch Comp Engn & Math Sydney NSW 2715 Australia

This paper investigates the problem of distributed H-8 filtering for a class of discrete-time Markov jump Lur'e systems over sensor networks with stochastic switching topologies. As a first effort, the redundant channels are considered to use in the data transmission to strive against the fragility of networks commonly configured by a single channel in the communication networks subject to quantization and randomly occurring packet dropouts. By constructing a Lur'e-type Lyapunov function interconnected with a cone-bounded nonlinearity, the filtering performance analysis for the underlying systems is carried out first. Then, a new class of distributed filters, which can be used to reflect the mismatching characteristic of modes jumping between the target plants and the proposed filters, is designed such that the filtering error system is stochastically stable and achieves a prescribed average H-8 performance index. A numerical example is provided to show the effectiveness of the proposed filtering scheme.

关键词： distributed filtering Markov jump Lur'e systems quantization random packet dropouts redundant channels stochastic switching topologies

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Robust distributed H∞ filtering over an uncertain sensor network with multiple fading measurements and varying sensor delays

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2020年第2期30卷 538-566页

作者： Hedayati, Mohammad Rahmani, Mehdi Imam Khomeini Int Univ Dept Elect Engn Qazvin Iran

In this paper, the problem of robust distributed H-infinity filtering is investigated for state-delayed discrete-time linear systems over a sensor network with multiple fading measurements, random time-varying communication delays, and norm-bounded uncertainties in all matrices of the system. The diagonal matrices, whose elements are individual independent random variables, are utilized to describe the multiple fading measurements. Furthermore, the Bernoulli-distributed white sequences are introduced to model the random occurrence of time-varying communication delays. In the proposed filtering approach, the stability of the estimation error system is first shown by the Lyapunov stability theory and the H-infinity performance is then achieved using a linear matrix inequality method. Finally, two numerical examples are given to show the effectiveness and performance of the proposed approach.

关键词： distributed filtering fading measurements LMI robust H-infinity filter time-varying delays uncertain sensor network

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distributed recursive filtering for stochastic systems under uniform quantizations and deception attacks through sensor networks

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AUTOMATICA 2017年 78卷 231-240页

作者： Ding, Derui Wang, Zidong Ho, Daniel W. C. Wei, Guoliang Univ Shanghai Sci & Technol Dept Control Sci & Engn Shanghai Key Lab Modern Opt Syst Shanghai 200093 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middx England City Univ Hong Kong Dept Math Kowloon Hong Kong Peoples R China

This paper is concerned with the distributed recursive filtering problem for a class of discrete time delayed stochastic systems subject to both uniform quantization and deception attack effects on the measurement outputs. The target plant is disturbed by the multiplicative as well as additive white noises. A novel distributed filter is designed where the available innovations are from not only the individual sensor but also its neighboring ones according to the given topology. Attention is focused on the design of a distributed recursive filter such that, in the simultaneous presence of time-delays, deception attacks and uniform quantization effects, an upper bound for the filtering error covariance is guaranteed and subsequently minimized by properly designing the filter parameters via a gradient-based method at each sampling instant. Furthermore, by utilizing the mathematical induction, a sufficient condition is established to ensure the asymptotic boundedness of the sequence of the error covariance. Finally, a simulation example is utilized to illustrate the usefulness of the proposed design scheme of distributed filters. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Sensor networks distributed filtering Recursive filtering Deception attacks Uniform quantization

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Adaptive event-triggered distributed recursive filtering with stochastic parameters and faults

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2022年第2期44卷 424-434页

作者： Wu, Lingling Ding, Derui Ju, Yamei Yi, Xiaojian Univ Shanghai Sci & Technol Coll Sci Shanghai Peoples R China Univ Shanghai Sci & Technol Dept Control Sci & Engn Shanghai Peoples R China Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China

This paper investigates the distributed recursive filtering issue of a class of stochastic parameter systems with randomly occurring faults. An event-triggered scheme with an adaptive threshold is designed to better reduce the communication load by considering dynamic changes of measurement sequences. In the framework of Kalman filtering, a distributed filter is constructed to simultaneously estimate both system states and faults. Then, the upper bound of filtering error covariance is derived with the help of stochastic analysis combined with basis matrix inequalities. The obtained condition with a recursive feature is dependent on the statistical characteristic of stochastic parameter matrices as well as the time-varying threshold. Furthermore, the desired filter gain is derived by minimizing the trace of the obtained upper bound. Finally, two simulation examples are conducted to demonstrate the effectiveness and feasibility of the proposed filtering method.

关键词： Adaptive event-triggering protocol stochastic parameters randomly occurring faults distributed filtering joint estimation

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distributed H∞ filtering for sensor networks with switching topology

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2013年第11期44卷 2104-2118页

作者： Zhang, Dan Yu, Li Song, Hongbo Wang, Qing-Guo Zhejiang Univ Technol Dept Automat Hangzhou 310032 Zhejiang Peoples R China Natl Univ Singapore Dept Elect & Comp Engn Singapore 119260 Singapore Natl Univ Singapore Dept Mech Engn Singapore 119260 Singapore

In this article, the distributed H filtering problem is investigated for a class of sensor networks under topology switching. The main purpose is to design the distributed H filter that allows one to regulate the sensor's working modes. Firstly, a switched system model is proposed to reflect the working mode change of the sensors. Then, a stochastic sequence is adopted to model the packet dropout phenomenon occurring in the channels from the plant to the networked sensors. By utilising the Lyapunov functional method and stochastic analysis, some sufficient conditions are established to ensure that the filtering error system is mean-square exponentially stable with a prescribed H performance level. Furthermore, the filter parameters are determined by solving a set of linear matrix inequalities (LMIs). Our results relates the decay rate of the filtering error system to the switching frequency of the topology directly and shows the existence of such a distributed filter when the topology is not varying very frequently, which is helpful for the sensor state regulation. Finally, the effectiveness of the proposed design method is demonstrated by two numerical examples.

关键词： distributed filtering sensor networks energy efficient switching topology exponentially stable LMIs

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Optimizing the dissemination of mobile agents for distributed information filtering

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IEEE CONCURRENCY 2000年第2期8卷 53-61页

作者： Theilmann, W Rothermel, K Univ Stuttgart Inst Parallel & Distributed High Performance Syst D-70565 Stuttgart Germany

Reduced communication costs can motivate programmers to use mobile agent technology. In this article, the authors analyze the use of mobile agents for filtering distributed information resources and present an approac... 详细信息

关键词： Mobile Agents Mobile Programs Dissemination Algorithms Information filtering distributed filtering

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Neural-network-based distributed security filtering for networked switched systems

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2022年第5期32卷 2791-2804页

作者： Shang, Hui Zong, Guangdeng Shi, Kaibo Qufu Normal Univ Sch Engn Rizhao 276826 Shandong Peoples R China Chengdu Univ Sch Informat Sci & Engn Chengdu Sichuan Peoples R China

In this paper, distributed security filtering is investigated for networked switched systems under the round-robin protocol (RRP). In order to fully take the practical situation into account, a cyber attack without additional bounded constraint is considered by introducing the neural network approximate technique. Moreover, the scattered sensor nodes are universally utilized to transmit and collect system information. The distributed filtering is proposed for the networked switched systems to estimate the system output. In order to ease data collisions, RRP is taken to schedule signal communication through the shared network. By constructing a token-dependent and mode-dependent Lyapunov function, sufficient conditions are given to ensure the filtering error system under cyber attack is finite-time bounded. The filtering gains are determined by solving a set of linear matrix inequalities. Finally, the availability of the acquired methods is verified by a PWM-driven boost converter model.

关键词： cyber attack distributed filtering networked switched systems round‐ robin protocol

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A Stochastic Sampled-Data Approach to distributed H_∞ filtering in Sensor Networks

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2011年第9期58卷 2237-2246页

作者： Shen, Bo Wang, Zidong Liu, Xiaohui Donghua Univ Sch Informat Sci & Technol Shanghai 200051 Peoples R China Brunel Univ Dept Informat Syst & Comp Uxbridge UB8 3PH Middx England

In this paper, the problem of distributed H-infinity filtering in sensor networks using a stochastic sampled-data approach is investigated. A set of general nonlinear equations described by sector-bounded nonlinearities is utilized to model the system and sensors in networks. Each sensor receives the information from both the system and its neighbors. The signal received by each sensor is sampled by a sampler separately with stochastic sampling periods before it is employed by the corresponding filter. By converting the sampling periods into bounded time-delays, the design problem of the stochastic sampled-data based distributed H-infinity filters amounts to solving the H-infinity filtering problem for a class of stochastic nonlinear systems with multiple bounded time-delays. Then, by constructing a new Lyapunov functional and employing both the Gronwall's inequality and the Jenson integral inequality, a sufficient condition is derived to guarantee the H-infinity performance as well as the exponential mean-square stability of the resulting filtering error dynamics. Subsequently, the desired sampled-data based distributed H-infinity filters are designed in terms of the solution to certain matrix inequalities that can be solved effectively by using available software. Finally, a numerical simulation example is exploited to demonstrate the effectiveness of the proposed sampled-data distributed H-infinity filtering scheme.

关键词： distributed filtering H-infinity filtering Jenson integral inequality sampled-data sensor networks stochastic sampling

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Probabilistic-constrained distributed fusion filtering for a class of time-varying systems over sensor networks: a torus-event-triggering mechanism

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2022年第6期53卷 1288-1297页

作者： Qu, Fanrong Zhao, Xia Wang, Xinmeng Tian, Engang Univ Shanghai Sci & Technol Coll Sci Shanghai 200093 Peoples R China Nanjing Univ Aeronaut & Astronaut Sch Automat Engn Nanjing 2111106 Peoples R China Univ Shanghai Sci & Technol Sch Opt Elect & Comp Engn Shanghai Peoples R China

This paper investigates the problem of distributed fusion over sensor networks with probabilistic constraints and stochastic perturbations. In order to save the bandwidth resources, a new event-triggering mechanism (ETM), called torus-event-triggering mechanism (TETM), is utilised for data transmission. Compared with the traditional ETMs, the TETM has two thresholds, which will not only discard the sampling data smaller than the lower threshold but also hold back the packet larger than the upper threshold. The main purpose of this paper is to design a time-varying distributed fusion filter such that: (1) the probability of the filtering error falling in a given ellipsoid domain is greater than a specified value and (2) the ellipsoidal set is minimised in the sense of matrix norm at each time point. To achieve the above-mentioned purpose, sufficient conditions are given to obtain the global fusion with the help of the recursive linear matrix inequality technique. The desired local filter parameters are then computed by solving an optimisation problem with some inequality constraints. Finally, a numerical simulation is given to illustrate the effectiveness and applicability of the proposed distributed fusion strategy.

关键词： Probabilistic constraint distributed filtering fusion sensor networks torus-event-triggering mechanism

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A new approach to distributed fusion filtering for networked systems with random parameter matrices and correlated noises

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INFORMATION FUSION 2019年 45卷 324-332页

作者： Caballero-Aguila, R. Hermoso-Carazo, A. Linares-Perez, J. Wang, Z. Univ Jaen Dept Estadist & IO Paraje Las Lagunillas S-N Jaen 23071 Spain Univ Granada Dept Estadist & IO Campus Fuentenueva S-N E-18071 Granada Spain Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middx England

This paper is concerned with the distributed filtering problem for a class of discrete-time stochastic systems over a sensor network with a given topology. The system presents the following main features: (i) random parameter matrices in both the state and observation equations are considered;and (ii) the process and measurement noises are one-step autocorrelated and two-step cross-correlated. The state estimation is performed in two stages. At the first stage, through an innovation approach, intermediate distributed least-squares linear filtering estimators are obtained at each sensor node by processing available output measurements not only from the sensor itself but also from its neighboring sensors according to the network topology. At the second stage, noting that at each sampling time not only the measurement but also an intermediate estimator is available at each sensor, attention is focused on the design of distributed filtering estimators as the least-squares matrix-weighted linear combination of the intermediate estimators within its neighborhood. The accuracy of both intermediate and distributed estimators, which is measured by the error covariance matrices, is examined by a numerical simulation example where a four-sensor network is considered. The example illustrates the applicability of the proposed results to a linear networked system with state-dependent multiplicative noise and different network-induced stochastic uncertainties in the measurements;more specifically, sensor gain degradation, missing measurements and multiplicative observation noises are considered as particular cases of the proposed observation model.

关键词： Sensor networks distributed filtering Random parameter matrices Correlated noises

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