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distributed estimation for uncertain systems subject to measurement quantization and adversarial attacks

INFORMATION FUSION 2025年 120卷

作者： Caballero-aguila, Raquel Hu, Jun Linares-Perez, Josefa Univ Jaen Jaen Spain Harbin Univ Sci & Technol Harbin Peoples R China Univ Granada Granada Spain

This study presents recursive algorithms for distributed estimation over a sensor network with a fixed topology, where each sensor node performs estimation using its own data as well as information from neighboring nodes. The algorithms are developed under the assumption that the sensor measurements are quantized and subject to random parameter variations, in addition to time-correlated additive noises. The network is assumed to be exposed to adversarial disruptions, specifically random deception attacks and denial-of-service (DoS) attacks. To address data loss due to DoS attacks, we introduce a compensation strategy that utilizes predicted values to preserve estimation reliability. In the proposed distributed estimation framework, each sensor local processor produces least-squares linear estimators based on both its own and neighboring sensor measurements. These initial estimators are termed early estimators, as those within the neighborhood of each node are subsequently fused in a second stage to yield the final distributed estimators. The algorithms rely on a covariance-based estimation approach that operates without specific structural assumptions about the dynamics of the signal process. A numerical experiment illustrates the applicability and effectiveness of the proposed algorithms and evaluates the effects of adversarial attacks on the estimation accuracy.

关键词： Networked uncertain systems distributed estimation Quantized measurements Time-correlated noise Adversarial attacks

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Secure distributed estimation via an average diffusion LMS and average likelihood ratio test

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DIGITAL SIGNAL PROCESSING 2025年 156卷

作者： Zayyani, Hadi Korki, Mehdi Qom Univ Technol QUT Qom Iran Swinburne Univ Technol Melbourne Australia

Secure distributed estimation algorithms are designed to protect against a spectrum of attacks by exploring different attack models and implementing strategies to enhance the resilience of the algorithm. These models encompass diverse scenarios such as measurement sensor attacks and communication link attacks, which have been extensively investigated in existing literature. This paper, however, focuses on a specific type of attack: the multiplicative sensor attack model. To counter this, the paper introduces the Average diffusion least mean square (ADLMS) algorithm as a viable solution. Furthermore, the paper introduces the Average Likelihood Ratio Test (ALRT) detector, which provides a straightforward detection criterion. In the presence of communication link attacks, the paper considers the manipulation attack model and presents an ALRT adversary detector. The analysis extends to these ALRT detectors, encompassing the calculation of adversary detection probability and false alarm probability, both achieved in closed form. The paper also provides the mean convergence analysis of the proposed ADLMS algorithm. Simulation results reveal that the proposed algorithms exhibit enhanced performance compared to the DLMS algorithm, while the incremental complexity remains only marginally higher than that of the DLMS algorithm.

关键词： distributed estimation Secure Averaging Likelihood ratio test Diffusion

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Diffusion random Fourier adaptive filtering algorithm based on logistic distance metric for distributed estimation

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DIGITAL SIGNAL PROCESSING 2025年 156卷

作者： Wu, Zhe Ni, Jingen Soochow Univ Sch Elect & Informat Engn Suzhou 215006 Peoples R China

distributed adaptive filtering over networks can improve filtering performance by fusing information from nodes within the same neighbor. In nonlinear estimation, adaptive filters derived from a linear framework usually suffer from large misalignment. To solve the above problem, this work develops a diffusion kernel filtering algorithm based on the random Fourier approximation method. To promote robustness to impulsive noise, the minimum logistic distance metric (LDM) is employed as a loss function. Compared to traditional kernel algorithms, the presented algorithm uses a fixed-length filter and is suitable for online distributed adaptive filtering tasks. In addition, this work also conducts a performance analysis based on Isserlis' and Price's theorems with several statistical assumptions. Simulations are conducted to exhibit the robustness of the proposed method to impulsive noise and to examine the accuracy of the theory on performance analysis.

关键词： distributed estimation Impulsive interference Kernel method Nonlinear system Logistic distance metric (LDM)

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Joint Measurement and Channel Design of a Malicious Sensor in distributed estimation Based on Maximum Disturbance in a Sensor Network

IEEE SENSORS LETTERS

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IEEE SENSORS LETTERS 2025年第1期9卷

作者： Zayyani, Hadi Salman, Mohammad Abu Hilal, Hasan Qom Univ Technol QUT Dept Elect Comp Engn Qom 12345 Iran Amer Univ Middle East Coll Engn & Technol Egaila 54200 Kuwait Higher Coll Technol Elect Engn Dept Abu Dhabi 25035 U Arab Emirates

Secure distributed estimation algorithms aim to be resilient against adversaries in a network. By deploying a single attacker with sufficiently large attack vectors in the network, the adversary can significantly degrade the performance of the estimator. Large attack vectors enhance the chance of attack detection. This letter aims to optimally design the measurement and channel attack vectors of a single attacker to maximally deviate the performance of the distributed estimation algorithm based on the maximum disturbance. A suboptimal joint measurement and channel attack design are provided using a Lagrange multipliers' method, in which the Lagrange multipliers are arbitrary and not obtained optimally. Subsequently, a suboptimal design for measurement-only and channel-only attacks is presented, with Lagrange multipliers derived mathematically. In fact, the false data injection (FDI) of a sensor has a profound effect on the performance of the distributed estimation in a sensor network. So, the action of even a single malicious sensor with deliberate attack design can degrade the true performance of the entire network. Simulation results demonstrate that these attack designs algorithms are more effective than random attack designs.

关键词： Sensor signal processing adversary attack diffusion distributed estimation disturbance Sensor signal processing adversary attack diffusion distributed estimation disturbance

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Prescribed-time distributed direct estimation under relative state measurements

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2025年第1期35卷 269-299页

作者： Ke, Jin Li, Ying Xie, Tao Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Dept Automat Shanghai 200240 Peoples R China

The distributed estimation technology is prevalently utilized to solve the leader-following multi-agent tracking problem. This technology poses a challenge in practice, since it generally relies on the available absolute state measurements. For this reason, a novel distributed estimation approach based on relative state measurements is developed in this article. The proposed method directly estimates the tracking error between the leader and each follower, rather than using an existing indirect way of estimating and making subtraction under absolute state measurements. Specifically, a distributed directed estimation is first studied to complete estimation tasks within prescribed time under the known directed networks. Then, a fully distributed directed estimation problem is considered under the unknown directed networks. Both distributed and fully distributed results are extended to the robustness cases to resist external disturbances. Simulation examples, including numerical examples and a multiship coordination example, are provided to demonstrate the effectiveness and advantages of the proposed distributed estimation method.

关键词： directed network distributed estimation multi-agent system prescribed time relative state robust adaptive method

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distributed estimation and control for nonlinear multi-agent systems in the presence of input delay or external disturbances

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ISA TRANSACTIONS 2020年第0期98卷 198-206页

作者： Jenabzadeh, Ahmadreza Safarinejadian, Behrouz Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

This paper establishes some distributed algorithms for nonlinear multi-agent systems to solve tracking control (TC) problem subject to external disturbances or delay. First, a distributed controller is introduced based on a distributed observer for the nodes to estimate and follow a nonlinear target. Then, utilizing a future predictor (FP) and an external disturbance observer, the proposed controller is developed for each agent with delay or disturbances to deal with TC problem. Stability of the control laws and FP is also analyzed and sufficient conditions are proposed for the TC of the multi-agent systems (MASs). Simulation examples validate the efficiency of the presented methods. (C) 2019 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Input delay distributed control External disturbances Multi-agent systems distributed estimation

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distributed estimation in Network Systems Using Event-Driven Receding Horizon Control

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2023年第9期68卷 5381-5396页

作者： Welikala, Shirantha Cassandras, Christos G. Univ Notre Dame Dept Elect Engn South Bend IN 46556 USA Boston Univ Div Syst Engn Brookline MA 02446 USA Boston Univ Ctr Informat & Syst Engn Brookline MA 02446 USA

We consider the problem of estimating the states of a distributed network of nodes (targets) through a team of cooperating agents (sensors) persistently visiting the nodes so that an overall measure of estimation error covariance evaluated over a finite period is minimized. We formulate this as a multiagent persistent monitoring problem where the goal is to control each agent's trajectory defined as a sequence of target visits and the corresponding dwell times spent making observations at each visited target. A distributed online agent controller is developed where each agent solves a sequence of receding horizon control problems (RHCPs) in an event-driven manner. A novel objective function is proposed for these RHCPs so as to optimize the effectiveness of this distributed estimation process and its unimodality property is established under some assumptions. Moreover, a machine learning solution is proposed to improve the computational efficiency of this distributed estimation process by exploiting the history of each agent's trajectory. Finally, extensive numerical results are provided indicating significant improvements compared to other state-of-the-art agent controllers.

关键词： Sensors Monitoring Trajectory estimation Linear programming Task analysis Space missions Control over network cooperative control distributed estimation event-driven control sensor networks

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distributed estimation based on quantized data

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IEICE ELECTRONICS EXPRESS 2011年第10期8卷 699-704页

作者： Kim, Yoon Hak Samsung Elect Syst LSI Div Gyeonggi Do 446711 South Korea

Since standard statistical estimation methods are built on the models that treat numerical data as continuous variables, they can be inappropriate and misleading when quantization process is involved in estimation. In this paper, we propose novel distributed estimation algorithms based on the Maximum Likelihood (ML) method. Motivated by the observation that each quantized measurement corresponds to a region with which the parameter to be estimated is associated, we develop algorithms that estimates the likelihood of each of the regions rather than that of the parameter itself. Our simulation results show that the proposed algorithms achieve good performance as compared with traditional ML estimators.

关键词： distributed estimation Maximum Likelihood (ML) Maximum A Posteriori (MAP) Kullback-Leibler (KL) divergence

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distributed estimation for Interconnected Systems With Arbitrary Coupling Structures

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2024年第4期11卷 3667-3677页

作者： Zhang, Yuchen Chen, Bo Yu, Li Ho, Daniel W. C. Zhejiang Univ Technol Dept Automat Hangzhou 310023 Peoples R China City Univ Hong Kong Dept Math Hong Kong 999077 Peoples R China

This paper is concerned with the problem of distributed estimation for time-varying interconnected systems with arbitrary coupling structures. A distributed stability condition requiring only the information from each subsystem and its neighbors is proposed to guarantee the stability of the designed distributed estimator. Then, a simplified condition without the real-time exchange of estimator gains is further proposed to reduce the communication burden. Under distributed stability constraints, the optimal estimator gain is designed by solving a convex optimization problem. Notice that the involved convex optimization problem can be easily solved by standard software packages because the constraints can be transformed into linear matrix inequalities. It is also shown that the designed distributed estimator is scalable for adding or subtracting subsystems. Finally, an illustrative example of a three-tank interconnected system is employed to show the effectiveness of the proposed methods.

关键词： Interconnected systems Stability analysis estimation Couplings Vectors Time-varying systems Optimization Time-varying interconnected system distributed stability condition distributed estimation optimal estimator convex optimization

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distributed estimation and Secondary Control of Autonomous Microgrid

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IEEE TRANSACTIONS ON POWER SYSTEMS 2017年第2期32卷 989-998页

作者： Zhang, Guoyue Li, Chaoyong Qi, Donglian Xin, Huanhai Zhejiang Univ Coll Elect Engn Hangzhou 310027 Peoples R China

This paper proposes a systematic approach to balance the active power between photovoltaic generators (PVs) and loads in autonomous microgrids. To achieve this, a distributed algorithm is designed to estimate the power difference between generation and consumption, then a finite-time consensus protocol is introduced to regulate the outputs of all the PVs in a cooperative and timely fashion, and the frequency deviation caused by active power unbalance can be compensated as well. In particular, the proposed distributed estimation and secondary control strategy is completely distributed and center-free in the sense that each PV and load are both self-organizing and global-awareness with only local communication, no centralized monitors are needed. Simulations on the standard IEEE 37-bus network are presented to verify the effectiveness of the proposed strategy.

关键词： Autonomous microgrid distributed estimation finite-time consensus secondary control

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