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distributed filtering for State-Saturated Systems With Switching Nonlinearities via Rayleigh Fading Channels: An Adaptive Event-Triggered Case

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INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING 2025年第4期39卷 785-802页

作者： Zhang, Qingbo Hu, Jun Liu, Desheng Zhu, Mingqing Yu, Hui Harbin Univ Sci & Technol Sch Automat Harbin Peoples R China Harbin Univ Sci & Technol Dept Appl Math Harbin Peoples R China Harbin Univ Sci & Technol Heilongjiang Prov Key Lab Optimizat Control & Inte Harbin Peoples R China Jiamusi Univ Sch Informat & Elect Technol Jiamusi Peoples R China Heilongjiang Acad Sci Inst Intelligent Mfg Harbin Peoples R China

The distributed filtering (DF) problem is investigated for state-saturated systems (SSSs) with switching nonlinearities under the adaptive event-triggered mechanism (AETM) and Rayleigh fading channels over sensor networks, where the data is transmitted between nodes through the Rayleigh fading channel. In addition, the AETM is introduced to save communication resources and improve data transmission efficiency. First, a distributed filter is designed incorporating the information of state saturation, switching nonlinearity, Rayleigh fading channel and AETM. Second, the upper bound (UB) on the filtering error covariance (FEC) is derived by the mathematical induction method, and the filter gain is obtained by minimizing the trace of the UB. Subsequently, the boundedness of UB on the FEC is shown through mathematical analysis. Finally, the effectiveness of the filtering scheme designed in this article is demonstrated through a numerical simulation example and a practical example, in which the influence of different Rayleigh parameters to the filtering performance and the superiority of using the AETM are discussed.

关键词： adaptive event-triggered mechanism distributed filtering Rayleigh fading channels state-saturated systems

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distributed filtering with time-varying topology: A temporal-difference learning approach in dual games

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SIGNAL PROCESSING 2025年 229卷

作者： Xue, Huiwen Wen, Jiwei Li, Ruichao Luan, Xiaoli Jiangnan Univ Sch Internet Things Engn Key Lab Adv Proc Control Light Ind Minist Educ Wuxi 214122 Peoples R China Northwestern Polytech Univ Sch Power & Energy Xian 710129 Peoples R China

This study aims to develop a dual games (DGs) mechanism and implement a temporal difference learning (TDL) approach to address distributed filter design while considering network-induced time-varying topology from individual optimality and global equilibrium perspectives. Ina detailed analysis, each filtering node (FN) treats its individual filtering action and exogenous disturbance as opposing elements, striving to determine the optimal policy while accounting for the worst-case scenario. This competition between FN and the disturbance culminates in a zero-sum game. Simultaneously, FN collaborates effectively with its neighbors to achieve consensus estimation, giving rise to a non-zero-sum game. Notably, an error-based filtering action is built to solve challenges posed by DGs. Ultimately, each FN attains its estimation at a minimum cost, and the entire distributed filtering network achieves the consensus estimation at a Nash equilibrium. Moreover, the transition probability correlation matrices (TPCMs) of the time-varying topology are obtained through direct observation of multi-episodes of topological transition trajectories. It has been proved that with a sufficiently ample number of episodes, TPCMs converge to their optimal values when TPs are known as apriori. Finally, a numerical example and an aero-engine system are presented to illustrate the effectiveness and practical potential of the proposed method.

关键词： Dual game distributed filtering Temporal difference learning Time-varying topology

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Probabilistic event-triggered distributed filtering for fuzzy systems under cyber-attacks

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INFORMATION SCIENCES 2025年 700卷

作者： Zhou, Zhidong Cai, Ying Cheng, Jun Wang, Yunliang Cao, Jinde Guangxi Normal Univ Sch Math & Stat Guilin 541006 Peoples R China Southeast Univ Sch Math Nanjing 211189 Peoples R China Ahlia Univ Manama 10878 Bahrain

This study addresses the distributed filtering problem in nonlinear systems under cyber-attacks, aiming to optimize bandwidth usage and improve system performance. A novel probabilistic event-triggered scheme (PETS) is proposed to reduce unnecessary network transmissions by leveraging time-varying characteristics of network-induced delays and dynamic triggering thresholds. To counteract the effects of channel noise and cyber-attacks, a state error filter with adaptive saturation levels is designed, dynamically adjusting its thresholds based on past estimation errors. Additionally, a piecewise T-S fuzzy distributed filter is developed, incorporating probabilistic delay division to address the complexities introduced by PETS. Sufficient conditions are established to ensure the stochastic stability and desired performance of the filtering error system (FES). The effectiveness and practicality of the proposed methods are validated through a simulation of a practical model.

关键词： distributed filtering Probabilistic event-triggered scheme (PETS) Cyber-attacks T-S fuzzy systems Dynamic saturation levels

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Protocol-Based distributed filtering for Stochastic Nonlinear Systems: Tackling Byzantine Attacks and Censored Measurements

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IEEE SENSORS JOURNAL 2025年第1期25卷 1029-1040页

作者： Meng, Xueyang Bai, Jianjun Chen, Yun Guo, Yunfei Hangzhou Dianzi Univ Sch Automat Hangzhou 310018 Peoples R China

This article focuses on the Byzantine-resilient distributed filtering problem for a class of stochastic nonlinear systems (SNSs) over sensor networks. The phenomenon of measurement censoring, which is depicted by a certain Tobit model with both left-censoring and right-censoring thresholds, is considered for the sensor outputs. To save limited network resources, the Round-Robin scheduling mechanism (RRSM) is deployed to govern data transmissions. A Byzantine attack model is introduced with which the Byzantine nodes manipulate the measurement signals arbitrarily before transmitting them to the neighbors. In this research, we endeavor to propose a Byzantine-resilient distributed filtering scheme that ensures an upper bound of filtering error variance and the stochastic boundedness of the resultant filtering error system. Such an upper bound is first calculated in terms of the solutions to coupled difference equations and then minimized by designing suitable filter parameters. Subsequently, the stochastic boundedness analysis issue is addressed for the filtering error dynamics. Finally, the validity of the obtained theoretical results is illustrated by a numerical example.

关键词： Wireless sensor networks Sensor phenomena and characterization Stochastic processes Upper bound Protocols Symmetric matrices Q measurement Noise measurement Vectors Nonlinear systems Byzantine attack censored measurement distributed filtering Round-Robin (RR) scheduling sensor network

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distributed filtering for T-S fuzzy systems under cyber-attacks with time-varying saturation function

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COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION 2025年 143卷

作者： Qiu, Yanping Cheng, Jun Zhou, Zhidong Cao, Jinde Guangxi Normal Univ Sch Math & Stat Guilin 541006 Peoples R China Southeast Univ Sch Math Nanjing 211189 Peoples R China

This paper focuses on the distributed filter issue for a class of nonlinear systems under hybrid cyber-attacks, encompassing both deception attacks and denial of service (DoS) attacks with uncertain attack probabilities. In the sensor network, each filter estimates the output signals of the systems by dealing with the output measurements from the systems and the information received from its neighbors and each filter may receive the state estimation information affected by outliers from its neighbors, which is propagated based on the communication topology. With the purpose of mitigating the effects from channel noise during the signal transmission on filtering error systems (FES) and the potential anomalies' impact in signal transmission caused by the hybrid cyber-attacks, a dynamic saturation function-based distributed filter is designed during the filtering process, whose saturation level is adaptively varying based on previous measurement errors. Through this approach and by utilizing Lyapunov-Krasovskii theory, sufficient conditions are established to ensure the stochastic stability (SS) of the FES and to achieve the predefined H infinity performance objectives. Finally, a practical model is presented to demonstrate the effectiveness and practicality of the designed distributed filter methodology.

关键词： distributed filtering T-S fuzzy model Dynamic saturation levels Hybrid cyber-attacks

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distributed filtering of nonlinear systems with memory-based dynamic event-triggering scheme

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JOURNAL OF THE FRANKLIN INSTITUTE 2025年第2期362卷

作者： Zhou, Zhidong Qiu, Yanping Cheng, Jun Cao, Jinde Wang, Yunliang Guangxi Normal Univ Sch Math & Stat Guilin 541006 Peoples R China Guangxi Normal Univ Ctr Appl Math Guangxi Guilin 541006 Peoples R China Southeast Univ Sch Math Nanjing 211189 Peoples R China Ahlia Univ Manama 10878 Bahrain

This study concerned with the distributed filtering issue of nonlinear systems subject to the memory-based dynamic event-triggering scheme (MBDETS) over sensor networks modeled by a set of linear Takagi-Sugeno (T-S) fuzzy models in the discrete-time domain. By absorbing historical triggered packets, a unified framework of MBDETS is developed, which is more capable of alleviating transmission frequency while achieving better performance. Additionally, a nonhomogeneous Markov process is suggested to relieve the communication rate by exploiting the time-varying characteristic, sufficient conditions are obtained to guarantee the stochastic stability of the resulting system by adopting the Lyapunov theories. At last, aiming at verifying the validity of achieved theoretical results, a practical model is applied in simulation section.

关键词： distributed filtering Nonhomogeneous Markov process Fuzzy systems Event-triggered scheme

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Necessary and sufficient condition of distributed H∞ filtering for interconnected large-scale systems: A novel space construction approach

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AUTOMATICA 2025年 171卷

作者： Yu, Tao Song, Jun Wu, Zhiying He, Shuping Anhui Univ Engn Res Ctr Autonomous Unmanned Syst Technol Sch Artificial Intelligence Minist Educ Hefei Peoples R China Chinese Acad Sci Hong Kong Inst Sci & Innovat Ctr Artificial Intelligence & Robot Hong Kong Peoples R China Anhui Univ Sch Elect Engn & Automat Informat Mat & Intelligent Sensing Lab Anhui Prov Hefei Peoples R China

This paper studies the distributed H-infinity filtering problem for interconnected large-scale systems (ILSs). In distributed filtering, all sub-filters are interconnected via the designed interconnection matrix and each filter only requires local subsystems' measurements to estimate the target signals. By the developed space construction method, novel both necessary and sufficient conditions are proposed to ensure the asymptotic stability and H performance of the filtering error ILSs. The novel conditions are numerically attractive because the computationally expensive matrix inversion terms are eliminated. In order to further reduce the computation burden, some sufficient conditions are also provided to guarantee the stability and H performance of the filtering error for ILSs. Then, by constructing the basis of the null space for some matrices skillfully and using Finsler's Lemma three times, this paper separates the product relation among the filter parameters and the unknown auxiliary variables. As a result, not only the filter parameters but also the interconnection matrix of distributed filters can be designed. The designed conditions are given in terms of linear matrix inequalities. At last, three examples are tested to demonstrate the advantages and superiorities of the developed filtering methodology. (c) 2024 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： distributed filtering Interconnected large-scale systems Matrix inversions Necessary and sufficient conditions

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Performance Analysis of distributed filtering under Misspecified Noise Covariances

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IEEE Transactions on Automatic Control 2025年

作者： Lyu, Xiaoxu Wen, Guanghui Shi, Ling Duan, Peihu Duan, Zhisheng The Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Southeast University School of Automation Nanjing 210096 China The Hong Kong University of Science and Technology Department of Chemical and Biological Engineering Hong Kong Beijing Institute of Technology State Key Laboratory of CNS/ATM Beijing 100081 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering Science College of Engineering Beijing 100871 China

This paper systematically investigates the performance of the consensus-based distributed filter under misspecified noise covariances. First, we introduce four quantities: the nominal filter parameter, the nominal estimation error covariance, the ideal filter parameter, and the ideal estimation error covariance. We derive the difference expressions among these quantities and establish the corresponding one-step relations. These relations reveal how performance deteriorates when noise covariances are misspecified, and demonstrate how to evaluate the estimation error covariance using the available nominal filter parameter. We particularly highlight the effect of the information fusion step number on these relations. Furthermore, recursive relations are introduced by extending the results of the one-step relations. Subsequently, we demonstrate the convergence of these quantities under the collective observability condition, and show that the convergence condition of the nominal filter parameter can guarantee the convergence of the estimation error covariance. Additionally, we provide bounds on the estimation error covariance under misspecified noise covariances by utilizing the Frobenius norms of the noise covariance deviations and the trace of the nominal filter parameter. Finally, the effectiveness of the theoretical results is verified through numerical simulations. © 1963-2012 IEEE.

关键词： consensus analysis convergence analysis distributed filtering misspecified noise covariance performance analysis

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distributed filtering for Markov jump systems with randomly occurring one-sided Lipschitz nonlinearities under Round-Robin scheduling

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NEUROCOMPUTING 2020年 417卷 396-405页

作者： Zhu, Mengze Chen, Yun Kong, Yaguang Chen, Cong Bai, Jianjun Hangzhou Dianzi Univ Zhejiang Sch Automat Key Lab IoT & Informat Fus Technol Hangzhou 310018 Peoples R China China Merchants Bank Transact Bank Dept Nantong Branch Nantong 226007 Peoples R China

This paper focuses on distributed filter design for Markov jump one-sided Lipschitz nonlinear systems over a sensor network by applying Round-Robin scheduling scheme. The nonlinear perturbations occur randomly and satisfy the so-called one-sided Lipschitz constraint that is more general than the conventional Lipschitz restraint. Two categories of exogenous noises, i.e., the persistent bounded noise and square additive noise in l(2) space, are taken into investigation, respectively. Meanwhile, the well-known Round-Robin scheduling protocol is employed to regulate the data transmission through the shared communication media. The exponential mean-square ultimate boundedness and stochastic bounded real lemma (BRL) are obtained for the filtering error dynamics, and then two distributed filters are correspondingly designed. Finally, an illustrative example shows the effectiveness of the proposed results. (C) 2020 Elsevier B.V. All rights reserved.

关键词： distributed filtering One-sided Lipschitz Randomly occurring nonlinearity Round-Robin protocol Sensor network

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distributed filtering Under Constrained Bit Rate Over Wireless Sensor Networks: Dealing With Bit Rate Allocation Protocol

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2023年第3期68卷 1642-1654页

作者： Li, Jun-Yi Wang, Zidong Lu, Renquan Xu, Yong Guangdong Univ Technol Sch Automat Guangzhou 510006 Peoples R China Guangdong Univ Technol Guangdong Prov Key Lab Intelligent Decis & Coopera Guangzhou 510006 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middx England

This article is concerned with the distributed filtering issue for linear discrete-time systems under bounded noises and constrained bit rate over wireless sensor networks. The communication between different sensor nodes is implemented via a wireless digital communication network with limited bandwidth. A bit rate constraint, which is subject to the so-called bandwidth allocation strategy, is placed to quantify the effect of the network bandwidth on the distributed filtering performance. An improved coding-decoding procedure is proposed to enable each node to decode messages from its neighbor nodes. Based on this procedure, a decoded-innovation-based distributed filtering scheme is put forward and a sufficient condition is established to ensure that the filtering error dynamics is ultimately bounded. Subsequently, a relationship between the bit rate and certain specific filtering performance is discovered. The desired parameters of the distributed filter are determined via solving two optimization problems whose objectives are actually the filtering performance indices including the smallest ultimate bound and the fastest decay rate. Furthermore, the codesign issue of the bit rate allocation protocol and the filter gain is converted into the mixed integer nonlinear programming problem, which is solved by means of the particle swarm optimization algorithm and the linear matrix inequality technique. Finally, numerical simulations on three scenarios are provided to verify the validity of the proposed distributed filtering approach.

关键词： Bit rate Wireless sensor networks Bandwidth Technological innovation Protocols Encoding Digital communication Coding-decoding scheme constrained bit rate distributed filtering ultimate boundedness wireless sensor network

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