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Power allocation scheme for distributed filtering over wireless sensor networks

IET CONTROL THEORY AND APPLICATIONS 2015年第3期9卷 410-417页

作者： Yang, Wen Shi, Hongbo E China Univ Sci & Technol Minist Educ Key Lab Adv Control & Optimizat Chem Proc Shanghai 200237 Peoples R China

In this work, distributed filtering over wireless sensor networks with limited energy is considered, where each sensor sends its local state estimate to its adjacent sensors through an unreliable wireless channel, which introduces random data packet drops. The packet drop rate depends on the power allocated by the sensor under an energy constraint. Several offline power scheduling strategies are introduced to distribute the power of sensors. A sufficient condition is provided to guarantee the convergence of network estimation error covariance. Further, an online power scheduling strategy is proposed, where each sensor utilises its real-time information to distribute energy for communications. The filtering performance of different power scheduling strategies are compared to show the influence of power distributed scheme on the expected state estimation error covariance.

关键词： wireless sensor networks wireless channels covariance analysis scheduling resource allocation filtering theory distributed filtering wireless sensor networks wireless channel packet drop rate offline power scheduling strategies network estimation error covariance online power scheduling strategy power distributed scheme state estimation error covariance

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Partial-Information-Based distributed filtering in Two-Targets Tracking Sensor Networks

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS 2012年第4期59卷 820-832页

作者： Huang, Chi Ho, Daniel W. C. Lu, Jianquan City Univ Hong Kong Dept Math Hong Kong Hong Kong Peoples R China Potsdam Inst Climate Impact Res D-14415 Potsdam Germany Southeast Univ Dept Math Nanjing 210096 Jiangsu Peoples R China

In this paper, the partial-information-based (PIB) distributed filtering problem is addressed for two-targets tracking sensor networks. Different from existing distributed filters, the information communication between the sensors are assumed to have an imperfect physical condition-only partial information can be transmitted. Furthermore, for different pairs of adjacent nodes, the partly transmitted information can be completely distinct. The constraint on "partial information transmission" makes the filtering problem in sensor networks more challenging and practical. Some criteria concerning the connection gains are derived and used to design efficient PIB distributed filter to achieve the following objectives: i) the sensor network can efficiently tract two desired targets in the absence of disturbance and noise;ii) the filter satisfies certain given performance constraint. By using the regrouping method, which is an effective way to derive the main results, some simple yet effective criteria are derived for PIB distributed filtering. A numerical example is utilized to illustrate the effectiveness of the theoretical results.

关键词： distributed filtering partial information sensor network two-targets tracking

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Probability-Guaranteed distributed filtering for Nonlinear Systems on Basis of Nonuniform Samplings Subject to Envelope Constraints

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IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2024年 10卷 905-915页

作者： Wang, Wei Hu, Chen Ma, Lifeng Yi, Xiaojian Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China Yangtze Delta Reg Acad Beijing Inst Technol Jiaxing Peoples R China

This paper investigates the probability-guaranteed distributed H-infinity filtering problem for stochastic time-varying systems over sensor networks. The measurements from sensing nodes are sampled nonuniformly before being received by filters and the sampling processes are modeled by a set of Markov chains. The purpose of the addressed problem is to design a distributed filter algorithm which meets the finite-horizon average H-infinity performance, meanwhile guaranteeing all filtering errors bounded within a prespecified envelope with a certain probability. Sufficient conditions for the feasibility of the mentioned filtering technique are established using convex optimization techniques. The desired filtering gains are subsequently determined by resolving the relevant matrix inequalities at each time step. Finally, the effectiveness of the proposed filtering algorithm is shown via an illustrative numerical example.

关键词： Sensors Noise Symmetric matrices Information processing Nonuniform sampling Nonlinear systems Matrix converters Vectors Time-varying systems State estimation Envelope-constrained in probability distributed filtering nonuniform sampling multiplicative noise sensor networks

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Probability-Guaranteed distributed filtering for Nonlinear Systems With Innovation Constraints Over Sensor Networks

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2021年第2期8卷 951-963页

作者： Ma, Lifeng Wang, Zidong Chen, Yun Yi, Xiaojian Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China Brunel Univ London Dept Comp Sci London UB8 3PH England Hangzhou Dianzi Univ Sch Automat Hangzhou 310018 Peoples R China Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China

In this article, the distributed filtering problem is investigated for a class of nonlinear systems. Each individual sensing node provides the state estimate by using not only its own measurements but also its neighbors' information propagated according to the communication topology. With the purpose of mitigating the effects from possible abnormal data during the signal transmission, an innovation constraint with adaptively determined threshold is imposed on the transmitted innovation during the filter process. The aim of the addressed problem is to design a distributed filtering algorithm, which is capable of confining all the estimation errors within certain ellipsoidal regions with prescribed probability and achieving the required average disturbance attenuation specification. By virtue of a convex optimization method, sufficient conditions are derived for the existence of the requested filtering algorithm, and the desired filtering parameters are then obtained by iteratively solving the corresponding matrix inequalities. Within the established framework, two optimization problems are put forward to seek locally optimal filtering parameters. Finally, an illustrative numerical example is provided to demonstrate the applicability of the proposed filtering paradigm.

关键词： distributed filtering innovation constraints probability-guaranteed filtering set-membership filtering

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Stochastic link activation for distributed filtering under sensor power constraint

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AUTOMATICA 2017年 75卷 109-118页

作者： Yang, Wen Yang, Chao Shi, Hongbo Shi, Ling Chen, Guanrong East China Univ Sci & Technol Key Lab Adv Control & Optimizat Chem Proc Minist Educ Shanghai Peoples R China Hong Kong Univ Sci & Technol Dept Elect & Comp Engn Hong Kong Hong Kong Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Hong Kong Peoples R China

We consider the problem of link activation for distributed estimation with power constraint. To satisfy the requirement of power consumption, we propose a stochastic link activation scheme, where each sensor equipped with a distributed estimator sends data to its neighboring sensors according to different probabilities. First, we design the optimal estimator gain of each sensor to minimize the state estimation error covariance. Then, we find an upper bound of the expected state estimation error covariance and provide a sufficient condition to guarantee the stability of the proposed estimator. Finally, we formulate the link activation problem as an optimization problem, and convert it to a convex optimization. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： distributed filtering Sensor scheduling Consensus Convex optimization

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Event-Based distributed filtering Over Markovian Switching Topologies

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2019年第4期64卷 1595-1602页

作者： Liu, Qinyuan Wang, Zidong He, Xiao Zhou, Donghua Tongji Univ Dept Comp Sci & Technol Shanghai 201804 Peoples R China Minist Educ Key Lab Embedded Syst & Serv Comp Shanghai 201804 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middx England Tsinghua Univ Dept Automat Beijing Natl Res Ctr Informat Sci & Technol Beijing 100084 Peoples R China Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Shandong Peoples R China Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

In this paper, we consider the distributed filtering problem for continuous-time stochastic systems over sensor networks subject to Markovian switching topologies. Due to limited communication energy and bandwidth, an event-based communication scheme is proposed with the aim to decrease the transmission frequency. An individual triggering condition is put forward to regulate the communication rates for each component of the system state in order to better reflect the engineering requirements. The aim of this paper is to design a distributed filter over sensor networks with Markovian switching topologies such that the dynamics of the estimation error is exponentially mean-square bounded. It is shown that, with the proposed event-based distributed filtering algorithm, the exponential mean-square boundedness of the estimation errors is guaranteed if the sensor network is distributively detectable and the combined communication topology is strongly connected. A numerical example is presented to illustrate the usefulness of the developed algorithm.

关键词： distributed filtering event-based scheme exponential boundedness Markovian switching topology sensor networks

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Scalable distributed filtering for a Class of Discrete-Time Complex Networks Over Time-Varying Topology

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2020年第8期31卷 2930-2941页

作者： Liu, Yang Wang, Zidong Zhou, Donghua Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middx England Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

This article is concerned with the distributed filtering problem for a class of discrete complex networks over time-varying topology described by a sequence of variables. In the developed scalable filtering algorithm, only the local information and the information from the neighboring nodes are used. As such, the proposed filter can be implemented in a truly distributed manner at each node, and it is no longer necessary to have a certain center node collecting information from all the nodes. The aim of the addressed filtering problem is to design a time-varying filter for each node such that an upper bound of the filtering error covariance is ensured and the desired filter gain is then calculated by minimizing the obtained upper bound. The filter is established by solving two sets of recursive matrix equations, and thus, the algorithm is suitable for online application. Sufficient conditions are provided under which the filtering error is exponentially bounded in mean square. The monotonicity of the filtering error with respect to the coupling strength is discussed as well. Finally, an illustrative example is presented to demonstrate the feasibility and effectiveness of our distributed filtering strategy.

关键词： Complex networks Topology Couplings Covariance matrices Heuristic algorithms Scalability Complex networks distributed filtering error boundedness monotonicity recursive algorithm time-varying topology

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A Recursive Matrix Inequality Approach to distributed filtering Over Binary Sensor Networks: Handling Amplify-and-Forward Relays

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第1期11卷 1347-1362页

作者： Han, Fei Wang, Zidong Liu, Hongjian Dong, Hongli Lu, Guoping Northeast Petr Univ Sanya Offshore Oil & Gas Res Inst Sanya 572025 Peoples R China Northeast Petr Univ Artificial Intelligence Energy Res Inst Daqing 163318 Peoples R China Northeast Petr Univ Heilongjiang Prov Key Lab Networking & Intelligent Daqing 163318 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH England Anhui Polytech Univ Minist Educ Key Lab Adv Percept & Intelligent Control High End Wuhu 241000 Peoples R China Anhui Polytech Univ Sch Math & Phys Wuhu 241000 Peoples R China Nantong Univ Sch Elect Engn Nantong 226019 Peoples R China

This article addresses the distributed filtering problem for a class of discrete time-varying systems over a binary sensor network (BSN) with amplify-and-forwarded (AF) relays, where the plant and binary measurements are subject to random noises that have known statistical information. The formulation of the topology of BSN with AF relays is first carried out. To reflect the dithering of the threshold of the binary sensor, a random variable with zero mean is utilized, and then useful information for estimation purposes is extracted by employing the joint distribution functions of measurement noises and the new random variable. Signal transmissions among neighbors are realized over fading channels, with a part of sensors communicating via relays. The desired distributed filter for each sensor is constructed using the available information from itself and its neighbors such that the resulting filtering error dynamics satisfies the desired exponential boundedness. To combat the fading effect, the relay matrix and the encoder matrix are designed in the sense of minimum mean square error so as to guarantee the effectiveness of the transmitted signal. The sufficient criterion for each sensor (with or without a relay) is established within the framework of the local performance analysis. The desired filter gains for each sensor are derived by solving a constrained optimization problem. Finally, an illustrative simulation example is used to demonstrate the applicability and effectiveness of the developed distributed filtering scheme.

关键词： Amplify-and-forward relays binary sensor network distributed filtering fading channel

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Energy Efficient distributed filtering for a Class of Nonlinear Systems in Sensor Networks

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IEEE SENSORS JOURNAL 2015年第5期15卷 3026-3036页

作者： Zhang, Dan Yu, Li Zhang, Wen-An Zhejiang Univ Technol Dept Automat Hangzhou 310023 Zhejiang Peoples R China

In this paper, the distributed filtering problem is investigated for a class of nonlinear systems in the wireless sensor networks. The main goal is to design a set of distributed filters and simultaneously to prolong the lifetime of networks. In order to save limited power in sensors, signal quantization is employed to reduce packet size, where the robust control approach is used to handle the quantization error. Then, the communication rate change is allowed and treated under a switched system model. Sufficient conditions are derived such that the filtering error system is exponentially stable in the mean-square sense and achieves a prescribed H-infinity performance level. The filter parameters are determined by solving an optimization problem. Finally, the effectiveness of the proposed results is demonstrated by two numerical examples.

关键词： distributed filtering energy efficient fuzzy systems sensor networks switched systems

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Event-based distributed filtering Approach to Nonlinear Stochastic Systems over Sensor Networks

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2019年第4期17卷 896-906页

作者： Hu, Zhongrui Shi, Peng Wu, Ligang Ahn, Choon Ki Harbin Inst Technol Res Inst Intelligent Control & Syst Harbin 150001 Heilongjiang Peoples R China Univ Adelaide Sch Elect & Elect Engn Adelaide SA 5005 Australia Korea Univ Sch Elect Engn 145Anam Ro Seoul 02841 South Korea

In this paper, an event-triggered communication strategy and a distributed filtering scheme are designed for discrete-time nonlinear stochastic systems over wireless sensor networks (WSNs). The underlying system is represented by the Takagi-Sugeno (T-S) fuzzy model, and in addition by the description of the WSN under consideration. The structure of the WSN is established on a deterministic one. Based on an event-triggering condition tailored for each sensor, distributed fuzzy filters are established using the triggered measurements of the smart sensors. As a result, an augmented stochastic system is presented for the distributed filtering design. A robust mean-square asymptotic stability criterion is explored using the Lyapunov stability theory and the Disk stability constraint is applied to improve the performance of the distributed filters. An optimization solution to obtaining the parameters of the distributed filters is developed. Subsequently, a computer-simulated example helps to illustrate the validity of the proposed new filtering design techniques.

关键词： distributed filtering event-triggered control fuzzy systems sensor networks

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