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Finite-Time Distributed Filtering of Time-Varying Switched Stochastic Systems With DoS Attacks Based on encoding-decoding scheme

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IEEE SYSTEMS JOURNAL 2023年第1期18卷 268页

作者： Fu, Hua Meng, Xueyang Chen, Yun Hangzhou Dianzi Univ Sch Automat Key Lab IoT & Informat Fus Technol Zhejiang Prov Hangzhou 310018 Peoples R China

This article is devoted to the finite-time distributed H-infinity filtering problem for a class of time-varying switched stochastic systems subject to denial-of-service (DoS) attacks over sensor networks. To fully utilize the limited network resources, an encoding-decoding scheme is introduced to facilitate the data transmissions through the sensor-to-filter channels. The Bernoulli random variables are utilized to characterize the DoS attacks occurring in a random way. The purpose of the tackled problem is to design a desired distributed filtering method such that both the stochastic finite-time boundedness and prescribed stochastic H-infinity performance are achieved for the resultant filtering error dynamics. On the basis of stochastic analysis method and average dwell time technique, the sufficient conditions are established to guarantee the existence of the desired filter for each node, and then, the proper filter parameters are calculated by solving a set of iterative matrix inequalities. Subsequently, a recursive distributed filtering algorithm is put forward that is suitable for online implementation. Finally, the validity of the obtained theoretical results is demonstrated by a numerical example.

关键词： Denial-of-service (DoS) attacks distributed H-infinity filtering encoding-decoding scheme stochastic finite-time boundedness (SFTB) switched stochastic systems

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Neural-Network-Based Secure State Estimation Under Energy-Constrained Denial-of-Service Attacks: An encoding-decoding scheme

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2023年第4期10卷 2002-2015页

作者： Zhang, Yuhan Wang, Zidong Zou, Lei Dong, Hongli Yi, Xiaojian Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middlesex England Donghua Univ Coll Informat Sci & Technol Shanghai 201620 Peoples R China Minist Educ Engn Res Ctr Digitalized Text & Fash Technol Shanghai 201620 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 Northeast Petr Univ Sanya Offshore Oil & Gas Res Inst Sanya 572024 Peoples R China Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China Beijing Inst Technol Yangtze Delta Reg Acad Jiaxing 314019 Peoples R China

This paper is concerned with the secure state estimation issue for a class of networked nonlinear systems under energy-constrained denial-of-service (EC-DoS) cyber-attacks and encoding-decoding scheme (EDS). The information transmissions between sensors and the estimator are executed via a bandwidth-limited communication network, on which the EDS is deployed to convert transmitted signals into finite-length codewords for the purpose of improving transmission efficiency. The EC-DoS attacks, whose intention is to jeopardize the network-based signal transmissions by overloading the communication resource, are assumed to occur in an intermittent way with bounded occurrence frequency/durations owing to the inherent energy constraints on the attackers. Considering the worst case of such EC-DoS attacks, a neural-network (NN)-based state estimator is constructed to generate the desired state estimates for the underlying networked nonlinear system. By employing the Lyapunov stability theory, the estimation error dynamics of the system state and the neural-network weight are jointly analyzed within a unified framework. Subsequently, sufficient conditions are obtained for the existence of the desired NN-based state estimator, and then both the desired estimator gain matrix and the NN tuning parameters are characterized. Finally, the validity of our estimation approach is confirmed by an example.

关键词： Networked nonlinear systems neural networks state estimation denial-of-service attacks encoding-decoding scheme

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Dynamic event-triggered state estimation for time-delayed spatial-temporal networks under encoding-decoding scheme

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NEUROCOMPUTING 2022年第0期500卷 868-876页

作者： Sun, Jie Shen, Bo Liu, Yurong Alsaadi, Fuad E. Donghua Univ Coll Informat Sci & Technol Shanghai 201620 Peoples R China Minist Educ Engn Res Ctr Digitalized Text & Fash Technol Shanghai 201620 Peoples R China Yangzhou Univ Dept Math Jiangsu 225002 Peoples R China King Abdulaziz Univ Fac Engn Dept Elect & Comp Engn Commun Syst & Networks CSN Res Grp Jeddah Saudi Arabia

This paper is concerned with the dynamic event-triggered state estimation problem for a class of spatial -temporal networks (STNs) with time-varying delays under an encoding-decoding strategy. For the sake of reducing the unnecessary resources wastes, we establish a dynamic event-triggered mechanism to deter-mine whether the current measurement output data is transmitted to the filter, where the threshold is dynamically adjusted according to a certain rule. In order to enhance the robustness of signal transmis-sion, an encoding-decoding strategy is exploited in the process of the data transmission. To be specific, the original signals encoded as a bit string are transmitted through binary symmetric channels with cer-tain crossover probabilities and then restored by a decoder at the receiver. By constructing Lyapunov-Krasovskii functional, we obtain a sufficient condition to ensure that the estimation error system is expo-nential mean square ultimately bounded. Subsequently, the desired state estimator is designed in terms of the solution to a certain matrix inequality. Finally, a numerical example is shown to demonstrate that the proposed state estimator is valid for time-delayed STNs. (c) 2022 Elsevier B.V. All rights reserved.

关键词： Dynamic event-triggered mechanism encoding-decoding scheme Spatial -temporal networks State estimation Time-delay

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Consensus-Based Distributed State Estimation Over Sensor Networks With encoding-decoding scheme: Accommodating Bandwidth Constraints

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2022年第6期9卷 4051-4064页

作者： Gao, Chen Wang, Zidong Hu, Jun Liu, Yang He, Xiao Tsinghua Univ Dept Automat BNRist Beijing 100084 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middx England Harbin Univ Sci & Technol Dept Math Heilongjiang Prov Key Lab Optimizat Control & Int Harbin 150080 Peoples R China Loughborough Univ Dept Aeronaut & Automot Engn Loughborough LE11 3TU Leics England

In this article, the consensus-based distributed estimation problem is investigated for linear time-invariant systems over sensor networks, where the sensors are required to estimate the system states in a cooperative manner through communication. A novel encoding-decoding scheme (EDS), which consists of two pairs of an innovation encoder/decoder and an estimation encoder/decoder, is proposed on each sensor to compress the data in order to accommodate the bandwidth-constrained network. An EDS-based consensus estimator is designed whose estimation performance is thoroughly discussed. Specially, a necessary and sufficient condition is established to ensure the convergence of the error dynamics of the state estimates, and then the boundedness issue of the size of the transmitted data is examined. Three optimization algorithms are provided for, respectively, the fastest convergence of the error dynamics, the minimization of the estimator gains, as well as the tradeoff between the convergence rate and the estimation deviation. The effectiveness of the developed distributed estimators is finally illustrated by a series of numerical examples.

关键词： Estimation Technological innovation Quantization (signal) Convergence Monitoring Topology State estimation decoding encoding Consensus estimation data size distributed state estimation encoding-decoding scheme sensor network

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Fuzzy modeling and event-triggered control of offshore platforms under constrained bandwidth: an encoding-decoding scheme

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NONLINEAR DYNAMICS 2025年 1-24页

作者： Yang, Yekai Niu, Yugang Li, Jiarui Donghua Univ Coll Informat Sci & Technol Shanghai Peoples R China East China Univ Sci & Technol Key Lab Smart Mfg Energy Chem Proc Shanghai Peoples R China Shanghai Maritime Univ Logist Engn Coll Dept Elect Automation Shanghai Peoples R China

This study investigates the fuzzy modeling and event-triggered control problems for nonlinear offshore platforms under encoding-decoding scheme (EDS), where an active mass damper (AMD) mitigates the platform vibrations induced by wave forces. First, the platform system with inherent nonlinearities is modeled via Takagi-Sugeno fuzzy technique. Under the limited bandwidth, event-triggering mechanism (ETM) and EDS are implemented for reducing communication resource usage. Given the distance between sensors installed on the platform and AMD, decentralized ETMs are developed to independently manage the signal transmission of each sensor. Besides, a dynamic quantizer and encoding function under limited coding length are deigned to convert triggered state into a binary string, i.e., codeword. Subsequently, a decoder is proposed to restore state signal and design fuzzy controller. Meanwhile, slack matrices integrated with membership function boundary information are utilized to derive sufficient conditions, and the relationship between control performance and coding error is clearly established. Finally, simulation results verify the vibration reduction performance in offshore platforms.

关键词： Nonlinear offshore platforms Takagi-Sugeno fuzzy model Event-triggered control Dynamic quantization encoding-decoding scheme

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Recursive State Estimation for Permanent Magnet Synchronous Motors With Sensor Degradations Under encoding-decoding schemes

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IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2024年第12期20卷 13687-13695页

作者： Li, Guhui Wang, Zidong Bai, Xingzhen Zhao, Zhongyi Wang, Yezheng Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH England Southeast Univ Sch Math Nanjing 210096 Peoples R China Nanjing Univ Informat Sci & Technol Sch Automat Nanjing 210044 Peoples R China

In this article, the state estimation problem is investigated for permanent magnet synchronous motors with sensor degradations under the encoding-decoding scheme. To reduce the network communication burden and enhance data transmission security, a uniform quantization-based encoding-decoding strategy is introduced in the sensor-to-estimator channel, which allows the transmitted power signals to be converted into digital format. Furthermore, the sensor degradation is represented by using a set of independent stochastic variables obeying uniform distributions. The primary objective of this article is to design a recursive state estimation algorithm such that, in the presence of sensor degradations and encoding-decoding strategy, a minimal upper bound on the estimation error covariance is derived by designing an appropriate estimator gain matrix. Simulation experiments for permanent magnet synchronous motors are conducted to validate the efficacy of the proposed recursive state estimation algorithm.

关键词： Degradation State estimation decoding encoding Stators Vectors Noise encoding-decoding scheme permanent magnet synchronous motor recursive state estimation sensor degradations uniform quantization

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encoding-decoding-based distributed state estimation over sensor networks with limited sensing range under DoS attacks

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NEUROCOMPUTING 2025年 611卷

作者： Lin, Xufeng Hu, Yanyan Zhang, Xuechun Peng, Kaixiang Univ Sci & Technol Beijing Sch Intelligence Sci & Technol Beijing 100083 Peoples R China Univ Sci & Technol Beijing Key Lab Intelligent Unmanned Syst Minist Educ Beijing 100083 Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China

This paper is concerned with encoding-decoding-based distributed state estimation over sensor networks under DoS attacks. Different from most of the existing research results on distributed state estimation for sensor networks, where all sensors are assumed to have sufficiently wide sensing ranges, this paper considers sensors with limited sensing ranges. Therefore, the problem studied has more practical significance. To save the limited bandwidth resources of sensor networks, a two-channel encoding-decoding scheme (EDS) based on probability is proposed for each node to compress the transmitted data to an acceptable range, where independent DoS attacks are launched randomly on the communication channels between nodes. Then, a distributed state estimator with limited sensing ranges under DoS attacks in the presence of both the sensor-estimator channel EDS and the node-node channel EDS is constructed under the criterion of minimum mean-square error. Furthermore, considering the real-time changes of the communication topology resulting from independent DoS attacks and the uncertainty introduced by the node-node channel EDS, the upper bound of the expected estimation error covariance is derived and the boundedness of the upper bound is analyzed under given assumption conditions. Finally, a numerical example is exhibited to illustrate the effectiveness of the designed algorithm.

关键词： Distributed state estimation DoS attacks Limited sensing range encoding-decoding scheme

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Recursive Filtering for Discrete-Time Stochastic Complex Networks Under Bit-Rate Constraints: A Locally Minimum Variance Approach

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2024年第5期69卷 3441-3448页

作者： Wang, Licheng Wang, Zidong Zhao, Di Liu, Yang Wei, Guoliang Shanghai Univ Elect Power Coll Automat Engn Shanghai 200090 Peoples R China Shandong Univ Sci & Technol Coll Elect Engn & Automat Qingdao 266590 Peoples R China Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middlesex England Univ Shanghai Sci & Technol Business Sch Shanghai 200093 Peoples R China Univ Huddersfield Sch Comp & Engn Huddersfield HD1 3DH England

In this article, the recursive filtering problem is investigated for a class of discrete-time stochastic dynamical networks where the data delivery from the sensors to the filter is implemented by a digital communication channel. With the help of the uniform quantization method, an improved encoding-decoding mechanism associated with measurement outputs is first put forward where the decoding error is guaranteed to be stochastically bounded under a certain bit-rate constraint condition. Based on the obtained decoded measurement outputs, sufficient conditions are then established such that the filtering error variance is constrained by an optimized upper bound at each sampling instant. The desired filter parameters are recursively calculated by solving two coupled Riccati difference equations. Moreover, the monotonicity for the filtering error variance with respect to the bit-rate of the communication channel is analytically discussed. Finally, an illustrative numerical simulation is provided to verify the obtained theoretical results.

关键词： Bit-rate constraint dynamical networks encoding-decoding scheme monotonicity analysis recursive filtering

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encoding-decoding-Based Distributed Fusion Filtering for Multi-Rate Nonlinear Systems With Sensor Resolutions

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IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2023年 9卷 811-822页

作者： Hu, Jun Fan, Shuting Chen, Cai Liu, Hongjian Yi, Xiaojian Harbin Univ Sci & Technol Dept Appl Math Harbin 150080 Peoples R China Harbin Univ Sci & Technol Sch Automat Harbin 150080 Peoples R China Harbin Univ Sci & Technol Key Lab Adv Mfg & Intelligent Technol Minist Educ Harbin 150080 Peoples R China Harbin Univ Sci & Technol Heilongjiang Prov Key Lab Optimizat Control & Inte Harbin 150080 Peoples R China Anhui Polytech Univ Sch Math Phys & Finance Wuhu 241000 Peoples R China Beijing Inst Technol Sch Mechatron Engn Beijing 100081 Peoples R China Yangtze Delta Reg Acad Beijing Inst Technol Jiaxing 314003 Peoples R China Beijing Inst Technol Tangshan Res Inst Tangshan 063099 Peoples R China

The paper investigates the distributed fusion filtering problem for time-varying multi-rate nonlinear systems (TVMRNSs) with sensor resolutions based on the encoding-decoding scheme (EDS) over sensor networks, where the iterative method is applied to the transformation of TVMRNSs. In order to enhance signal interference-resistant capability and improve transmission efficiency, the EDS based on dynamic quantization is introduced during the measurement transmission. On the basis of the decoded measurements, a local distributed filter is constructed, where an upper bound on the local filtering error (LFE) covariance is derived and the local filter gains are obtained by minimizing the trace of the upper bound. Subsequently, the fusion filtering algorithm is presented according to the covariance intersection fusion criterion. In addition, a sufficient condition is provided via reasonable assumptions to ensure the uniform boundedness of the upper bound on the LFE covariance. Finally, a moving target tracking practical example is taken to show the superiority of the proposed filtering algorithm and discuss the monotonicity of the mean-square error of the fusion filter with respect to the sensor resolutions and quantization intervals.

关键词： Quantization (signal) Estimation Nonlinear systems Distortion measurement Time-varying systems Upper bound Security Sensor networks multi-rate sampling sensor resolutions encoding-decoding scheme covariance intersection fusion

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encoding-decoding-based fusion estimation with filter-and-forward relays and stochastic measurement delays

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INFORMATION FUSION 2023年第1期100卷

作者： Liu, Yang Wang, Zidong Lin, Hong Ma, Lifeng Lu, Guoping Univ Huddersfield Dept Comp Sci Huddersfield HD1 3DH England Brunel Univ London Dept Comp Sci Uxbridge UB8 3PH Middx England Shenzhen Polytech Inst Intelligence Sci & Engn Shenzhen 518055 Peoples R China Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China Nantong Univ Sch Elect Engn Nantong 226019 Peoples R China

This paper addresses the encoding-decoding-based fusion estimation problem for a class of systems with signal relays and stochastic measurement delays. A set of Bernoulli distributed random variables is used to model the randomly occurring measurement delays. To enhance the system performance and extend the transmission distance, a filter-and-forward relay is adopted in the transmission link. To handle the limited bandwidth of the communication channels, an encoding-decoding scheme based on a probabilistic quantizer is proposed for the sensor-relay and relay-estimator channels. For each relay, a local filter is constructed with a proper filter gain at each time step with aim to minimize an upper bound of the local estimation error covariance. The effects of the encoding-decoding scheme on the error covariance are also analyzed quantitatively. The estimates obtained from the local filters are then fused at the remote estimator using the covariance intersection fusion strategy. Finally, a target tracking simulation example is presented to demonstrate the effectiveness of the proposed framework.

关键词： Fusion estimation Filter-and-forward relay encoding-decoding scheme Covariance intersection fusion Measurement delay Recursive algorithm

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