IEEE Transactions on Control of Network Systems最新文献

Event-Based Secure Control for Cyber-Physical Power Systems Under Stochastic DoS Attacks 随机DoS攻击下基于事件的网络物理电力系统安全控制

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-03-11 DOI: 10.1109/TCNS.2026.3691753

Rongni Yang;Ruifeng Zhang;Yanzheng Zhu;Yi Yu

{"title":"Event-Based Secure Control for Cyber-Physical Power Systems Under Stochastic DoS Attacks","authors":"Rongni Yang;Ruifeng Zhang;Yanzheng Zhu;Yi Yu","doi":"10.1109/TCNS.2026.3691753","DOIUrl":"https://doi.org/10.1109/TCNS.2026.3691753","url":null,"abstract":"In this article, a new dynamic event-triggered secure control problem for the cyber-physical power systems (CPPSs) under stochastic denial-of-service (DoS) attacks is studied. Particularly, the considered DoS attacks are characterized by the stochastic property with periodic occurrences, such that a class of discrete-time cyclic dwell-time Markov systems with both stable and unstable subsystems is presented to model the concerned CPPSs under these DoS attacks. Meanwhile, a novel dual-mode dynamic event-triggered mechanism that works in both nonattack and attack scenarios is introduced to save limited network resources. Next, the stochastic stability and <inline-formula><tex-math>$H_{infty }$</tex-math></inline-formula> performance analysis are carried out for the augmented systems by establishing a cyclic piecewise Markov Lyapunov function with greater design freedom, and the explicit controller is designed to ensure the security of the considered CPPSs. Finally, the applications of 1,3-area CPPSs under stochastic DoS attacks with periodic occurrences are illustrated to verify the effectiveness and advantage of the proposed control method.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"13 3","pages":"1509-1520"},"PeriodicalIF":5.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Game-Theoretic Coordination for Time-Critical Missions of UAV Systems 无人机系统时间关键任务的博弈论协调

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-06-22 DOI: 10.1109/TCNS.2026.3705999

Mikayel Aramyan;Anna Manucharyan;Lusine Poghosyan;Tigran Bakaryan;Naira Hovakimyan

{"title":"Game-Theoretic Coordination for Time-Critical Missions of UAV Systems","authors":"Mikayel Aramyan;Anna Manucharyan;Lusine Poghosyan;Tigran Bakaryan;Naira Hovakimyan","doi":"10.1109/TCNS.2026.3705999","DOIUrl":"https://doi.org/10.1109/TCNS.2026.3705999","url":null,"abstract":"Coordinated missions involving uncrewed aerial vehicles (UAVs) in dynamic environments pose significant challenges in maintaining both coordination and agility. In this article, relying on the cooperative path following framework and using a game-theoretic formulation, we introduce a novel and scalable approach in which each UAV acts autonomously in different mission conditions. This formulation naturally accommodates heterogeneous and time-varying objectives across the system. In our setting, each UAV optimizes a cost function that incorporates temporal and mission-specific constraints. The optimization is performed within a 1-D domain, significantly reducing the computational cost and enabling real-time application to complex and dynamic scenarios. The framework is distributed in structure, enabling global, system-wide coordination (a Nash equilibrium) by using only local information. For ideal systems, we prove the existence, and the Nash equilibrium exhibits exponential convergence. Furthermore, we invoke model predictive control for nonideal scenarios. In particular, we propose a discrete-time optimization approach that tackles path-following errors and communication failures, ensuring reliable and agile performance in dynamic and uncertain environments. Simulation results demonstrate the effectiveness and agility of the approach in ensuring successful mission execution across diverse realistic scenarios.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"13 3","pages":"1822-1834"},"PeriodicalIF":5.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed Fault-Tolerant Consensus Control for Multiagent Systems With an Event-Triggered Differential Privacy Strategy 基于事件触发差分隐私策略的多智能体系统分布式容错一致性控制

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-03-12 DOI: 10.1109/TCNS.2026.3691763

Yiliu Liu;Chun Liu;Xiaoqiang Ren;Jianglin Lan;Xiaofan Wang

{"title":"Distributed Fault-Tolerant Consensus Control for Multiagent Systems With an Event-Triggered Differential Privacy Strategy","authors":"Yiliu Liu;Chun Liu;Xiaoqiang Ren;Jianglin Lan;Xiaofan Wang","doi":"10.1109/TCNS.2026.3691763","DOIUrl":"https://doi.org/10.1109/TCNS.2026.3691763","url":null,"abstract":"This study investigates the problem of privacy-preserving fault-tolerant consensus control (FTCC) for discrete-time linear multivariate multiagent systems affected by actuator loss-of-effectiveness faults and eavesdropping threats. To tackle this issue, two novel distributed FTCC schemes incorporating an event-triggered differential privacy strategy (ETDPS) are proposed, wherein the ETDPS first perturbs the state of each agent by injecting random noise and subsequently determines whether to transmit the perturbed state based on an event-triggering condition with a state-independent triggering threshold. This strategy is designed to prevent the disclosure of initial states of agents to potential eavesdroppers while reducing the communication overhead induced by continuous transmissions. Building upon the ETDPS, two fault-tolerant consensus controllers are developed in a distributed manner, both of which guarantee consensus despite the presence of actuator degradation. The privacy level of the first controller is intrinsically determined by the system dynamics, whereas the second further enhances privacy by embedding a noise feedback mechanism into the control protocol. Sufficient conditions are derived to achieve mean-square consensus and <inline-formula><tex-math>$epsilon$</tex-math></inline-formula>-differential privacy via matrix norm analysis. Simulation results validate the feasibility of the proposed ETDPS-based FTCC schemes.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"13 3","pages":"1581-1591"},"PeriodicalIF":5.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed Conjugate-Gradient Tracking With Prescribed Performance for Multiagent Convex Optimization 多智能体凸优化的给定性能分布共轭梯度跟踪

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-07-06 DOI: 10.1109/TCNS.2026.3710316

Spyridon Garmpis;Charalampos P. Bechlioulis

{"title":"Distributed Conjugate-Gradient Tracking With Prescribed Performance for Multiagent Convex Optimization","authors":"Spyridon Garmpis;Charalampos P. Bechlioulis","doi":"10.1109/TCNS.2026.3710316","DOIUrl":"https://doi.org/10.1109/TCNS.2026.3710316","url":null,"abstract":"This article introduces a continuous-time distributed conjugate-gradient tracking algorithm with prescribed performance guarantees for constrained convex optimization in multiagent systems. Building upon recent developments in distributed conjugate-gradient methods, the proposed approach enables agents to cooperatively estimate the average conjugate direction using only locally available information through an adaptive dynamic consensus mechanism. Prescribed performance is enforced via a dynamic average consensus scheme that ensures predefined transient and steady-state tracking behavior through explicit parameter tuning. Local inequality constraints are handled by embedding logarithmic barrier penalty functions into the agents' objective functions. Using Lyapunov-based stability analysis and convex optimization theory, practical exponential convergence to a predefined arbitrarily small neighborhood of the global optimizer is established under an undirected communication topology. Numerical simulations demonstrate improved convergence speed and reduced communication requirements compared to existing continuous-time gradient tracking and momentum-based methods, with effectiveness illustrated in fixed-time constrained multiagent scenarios.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"13 3","pages":"1861-1873"},"PeriodicalIF":5.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11595494","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Finite-Sample System Identification of Linear Systems Under Random Packet Loss 随机丢包情况下线性系统的有限样本辨识

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-03-07 DOI: 10.1109/TCNS.2026.3691227

Tianyang Tian;Zhenning Zhang;Liang Xu

{"title":"Finite-Sample System Identification of Linear Systems Under Random Packet Loss","authors":"Tianyang Tian;Zhenning Zhang;Liang Xu","doi":"10.1109/TCNS.2026.3691227","DOIUrl":"https://doi.org/10.1109/TCNS.2026.3691227","url":null,"abstract":"This article investigates finite-sample system identification for discrete-time linear systems subject to random data packet loss. Random data packet loss destroys the usual linear structure of least squares identification, which makes classical nonasymptotic analyses inapplicable. We address this difficulty by viewing the resulting nonlinear least squares estimator as an empirical loss minimizer and developing a statistical learning-based framework to study its performance under packet loss. Under mild assumptions, we derive high-probability finite-sample guarantees for the generalization error that reveal how identification performance improves as more samples are collected, but tends to deteriorate for higher dimensional systems and for longer bursts of packet loss, especially when the underlying dynamics are only weakly stable. By further imposing a local identifiability and strong-convexity condition around the true system matrices, we translate these generalization guarantees into nonasymptotic bounds on the parameter estimation error, which exhibit the same qualitative trends and show that longer packet loss worsen the constants in the bounds, so that more data are required to achieve a given accuracy. The numerical simulation verified the conclusion.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"13 3","pages":"1284-1295"},"PeriodicalIF":5.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributed Fusion With Global and Local Variables 具有全局和局部变量的分布式融合

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-03-08 DOI: 10.1109/TCNS.2026.3691472

Giorgio Battistelli;Luigi Chisci;Nicola Forti

{"title":"Distributed Fusion With Global and Local Variables","authors":"Giorgio Battistelli;Luigi Chisci;Nicola Forti","doi":"10.1109/TCNS.2026.3691472","DOIUrl":"https://doi.org/10.1109/TCNS.2026.3691472","url":null,"abstract":"This article presents a distributed fusion framework for probabilistic models with global and local variables, addressing scalable model aggregation in decentralized systems. The approach employs a conditional representation, expressing the probability density function (PDF) of global variables conditioned on local variables, supplemented by the marginal PDF of the local variables. By extending the logarithmic opinion pooling rule to this representation, the framework enables efficient fusion of probabilistic models using practical distributed protocols, such as flooding and consensus. It supports closed-form solutions for exponential family distributions and particle-based representations, leveraging a Rao–Blackwellized particle filter to marginalize local variables via particle filtering while maintaining analytical tractability for global variables. The framework is applied to distributed object tracking with multisensor registration. Simulations demonstrate near-centralized performance, validating the framework’s scalability and effectiveness in fully decentralized environments.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"13 3","pages":"1347-1359"},"PeriodicalIF":5.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11512986","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Trust-Driven and Interaction-Driven Resilient Distributed Secure Learning Algorithm and Its Application 信任驱动和交互驱动的弹性分布式安全学习算法及其应用

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-03-11 DOI: 10.1109/TCNS.2026.3691761

Fuxi Niu;Xiaohong Nian;Te Ma;Shiling Li;Yong Chen;Maolong Lv

引用次数: 0

Interplay Between Graph Spectrum and Fast Consensus in Multiagent Systems With Artificial Delays 具有人工延迟的多智能体系统图谱与快速一致性的相互作用

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-03-08 DOI: 10.1109/TCNS.2026.3691481

Alejandro Martínez-González;Adrián Ramírez

{"title":"Interplay Between Graph Spectrum and Fast Consensus in Multiagent Systems With Artificial Delays","authors":"Alejandro Martínez-González;Adrián Ramírez","doi":"10.1109/TCNS.2026.3691481","DOIUrl":"https://doi.org/10.1109/TCNS.2026.3691481","url":null,"abstract":"This article presents a single-delay proportional-retarded consensus protocol that improves the speed of response in a large-scale multiagent system with <inline-formula><tex-math>$n$</tex-math></inline-formula> double integrators. Unlike its predecessor with multiple delays, the proposed protocol uses a single delay across the network, eliminating the need to implement <inline-formula><tex-math>$n-1$</tex-math></inline-formula> incommensurate delays. This simplification is achieved without compromising the protocol’s established properties, including fast consensus, minimal system information requirements, and robustness to measurement noise. The main result establishes that optimizing the spectral abscissa of the collective dynamics determines consensus speed. While this optimization is generally intractable due to the system’s infinite-dimensional nature, in undirected networks, the problem becomes solvable in closed form by analyzing the stability of only two key quasi-polynomials: one associated with the algebraic connectivity and the other with the spectral radius of the graph’s Laplacian. This approach extends to arbitrarily large networks, leading to a scalable analytical tuning rule for the protocol parameters.","PeriodicalId":56023,"journal":{"name":"IEEE Transactions on Control of Network Systems","volume":"13 3","pages":"1385-1398"},"PeriodicalIF":5.3,"publicationDate":"2026-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148985668","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Finite-Time Distributed Time-Varying Optimization of High-Order Agents With Unknown Gradient Derivative 梯度导数未知的高阶智能体的有限时间分布时变优化

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-06-08 DOI: 10.1109/TCNS.2026.3701555

Wenbo Zhu;Shu Liang

引用次数: 0

Robust Distributed Model-Predictive Control Based on Self-Triggered Mechanism for Nonlinear Asynchronous Multiagent Systems 基于自触发机制的非线性异步多智能体系统鲁棒分布模型预测控制

IF 5.3 3区计算机科学

IEEE Transactions on Control of Network Systems Pub Date : 2026-09-01 Epub Date: 2026-03-12 DOI: 10.1109/TCNS.2026.3691809

Yang Peng;Huaicheng Yan;Tinghan Jia;Li Wang;Yuyan Wu;Guangjing Song

引用次数: 0