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IEEE International Conference on Networking, Sensing and Control

作者： Guo-Lin Sun Wei Guo National Communication Technology Key Laboratory University of Electronic Science and Technology Chengdu China

ISBN: (纸本)0780381939

Determining where a given unknown node is physically located in a sensor network is known as the problem of localization, which is challenging and yet extremely crucial for many applications. In this paper, we propose some distributed, scalable and probabilistic localization algorithms with one mobile beacon and present a simple mobile beacon-driven communication protocol. In our method, every unknown sensor node receiving beacon packets estimates its own position using parametric and non-parametric probabilistic estimation techniques. Furthermore, we compare several distributed algorithms through simulation experiments, which reveal that non-parametric probabilistic estimation is more robust and accurate than ordinary methods. Finally, we explore the impact of several factors on localization accuracy based on our method.

关键词： Wireless sensor networks Maximum likelihood estimation Global Positioning System Communications technology Costs RF signals Sun Protocols distributed algorithms Robustness

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distributed BFS algorithms

Distributed BFS algorithms

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Annual IEEE Symposium on Foundations of Computer Science

作者： Baruch Awerbuch Robert G. Gallager MIT

This paper develops a new distributed BFS algorithm for an asynchronous communication network. This paper presents two new BFS algorithms with improved communication complexity. The first algorithm has complexity O((E+V1.5)·logV) in communication and O(V1.5·logV) in time. The second algorithm uses the technique of the first recursively and achieves O(E·2 √logVloglogV) in communication and O(V·2√logVloglogV) in time.

关键词： distributed algorithms Propagation delay Bandwidth Asynchronous communication Complexity theory Particle separators Video recording Web sites Internet Interactive systems

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A Tutorial on distributed Optimization for Cooperative Robotics: From Setups and algorithms to Toolboxes and Research Directions

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PROCEEDINGS OF THE IEEE 2025年第1期113卷 40-65页

作者： Testa, Andrea Carnevale, Guido Notarstefano, Giuseppe Univ Bologna Dept Elect Elect & Informat Engn I-40136 Bologna Italy

Several interesting problems in multirobot systems can be cast in the framework of distributed optimization. Examples include multirobot task allocation, vehicle routing, target protection, and surveillance. While the theoretical analysis of distributed optimization algorithms has received significant attention, its application to cooperative robotics has not been investigated in detail. In this article, we show how notable scenarios in cooperative robotics can be addressed by suitable distributed optimization setups. Specifically, after a brief introduction on the widely investigated consensus optimization (most suited for data analytics) and on the partition-based setup (matching the graph structure in the optimization), we focus on two distributed settings modeling several scenarios in cooperative robotics, i.e., the so-called constraint-coupled and aggregative optimization frameworks. For each one, we consider use-case applications, and we discuss tailored distributed algorithms with their convergence properties. Then, we revise state-of-the-art toolboxes allowing for the implementation of distributed schemes on real networks of robots without central coordinators. For each use case, we discuss its implementation in these toolboxes and provide simulations and real experiments on networks of heterogeneous robots.

关键词： Optimization Robots Multi-robot systems Robot kinematics Surveillance Resource management distributed algorithms Tutorials Formation control Vehicle routing Cooperating robots distributed optimization distributed robot systems optimization and optimal control

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Asynchronous distributed Nonsmooth Composite Optimization via Computation-Efficient Primal-Dual Proximal algorithms

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IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE 2025年第2期9卷 1595-1609页

作者： Ran, Liang Li, Huaqing Zheng, Lifeng Li, Jun Southwest Univ Coll Elect & Informat Engn Chongqing Key Lab Nonlinear Circuits & Intelligent Chongqing 400715 Peoples R China

This paper focuses on a distributed nonsmooth composite optimization problem over a multiagent networked system, in which each agent is equipped with a local Lipschitz-differentiable function and two possibly nonsmooth functions, one of which incorporates a linear mapping. To address this problem, we introduce a synchronous distributed algorithm featuring uncoordinated relaxed factors. It serves as a generalized relaxed version of the recent method TriPD-Dist. Notably, the considered problem in the presence of asynchrony and delays remains relatively unexplored. In response, a new asynchronous distributed primal-dual proximal algorithm is first proposed, rooted in a comprehensive asynchronous model. It is operated under the assumption that agents utilize possibly outdated information from their neighbors, while considering arbitrary, time-varying, yet bounded delays. With some special adjustments, new asynchronous distributed extensions of existing centralized methods are obtained via the proposed asynchronous algorithm. Theoretically, a new convergence analysis technique of the proposed algorithms is provided. Specifically, a sublinear convergence rate is explicitly derived by showcasing that the iteration behaves as a nonexpansive operator. In addition, the proposed asynchronous algorithm converges the optimal solution in expectation under the same step-size conditions as its synchronous counterpart. Finally, numerical studies substantiate the efficacy of the proposed algorithms and validate their performance in practical scenarios.

关键词： Delays Optimization distributed algorithms Convergence Vectors Convex functions Computational intelligence Asynchrony delayed communication nonsmooth convex functions distributed optimization algorithm

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Sign Hessian-Weighted Gradient algorithms for distributed Time-Varying Convex Optimization

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2025年第1期12卷 474-484页

作者： Huang, Bomin Yang, Chengqian Chen, Fei Lan, Weiyao Jimei Univ Coll Comp Engn Xiamen 361021 Peoples R China Northeastern Univ Qinhuangdao Sch Control Engn Qinhuangdao 066004 Peoples R China Nankai Univ Coll Artificial Intelligence Tianjin 300350 Peoples R China Xiamen Univ Dept Automat Xiamen 361005 Peoples R China

In this article, we initiate our exploration with a time-varying optimization problem, featuring linear equality constraints. To address this complex problem, we introduce a novel continuous-time sign Hessian-weighted gradient algorithm. Remarkably, our proposed approach is capable of handling the time-varying nature of the problem, all without the need for the invertibility of the Hessian matrix associated with the cost function. We present two distinct distributed algorithms: the edge-based and node-based variations. To underscore the practical effectiveness of our methodology, we provide some numerical examples, offering compelling evidence to validate our research findings.

关键词： Cost function Heuristic algorithms Vectors Network systems Time-varying systems distributed algorithms Control systems Convergence Transportation Surges distributed algorithm Hessian matrix sign function time-varying optimization

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distributed Proportional-Integral algorithms for Multiple Coalition Games Under Limited Communication Resources

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IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2025年 11卷 450-459页

作者： Liu, Jiaxun Wang, Dong Liu, Jiashuo Dong, Xiwang Ludong Univ Sch Math & Stat Sci Yantai 264025 Peoples R China Minist Educ Key Lab Intelligent Control & Optimizat Ind Equipm Dalian 116024 Peoples R China Dalian Univ Technol Sch Control Sci & Engn Dalian 116024 Peoples R China Beihang Univ Inst Unmanned Syst Inst Artificial Intelligence Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

This paper studies the algorithm design for multiple coalition games under limited communication resources, in which the players in the same coalition cooperatively optimize the summation of cost functions in this coalition and do not care about the costs of other coalitions. To address this game, we develop a distributed proportional-integral algorithm based on the coalition estimate strategy and the proportional-integral principle. Furthermore, when the communication resource is concretely quantified by bit rates in communication channels, we propose a coding-decoding-based distributed proportional-integral algorithm based on the distributed proportional-integral algorithm and coding-decoding rules for seeking the Nash equilibrium of multiple coalition games. It proves that both algorithms linearly and precisely converge to the Nash equilibrium in spite of limited communication resources. Then, the necessary and sufficient condition for the linear convergence of the proposed algorithm about the requirement of bit rates is presented. Moreover, the relationship between the bit rate and the convergence speed of the proposed algorithm is also theoretically explained. Lastly, the simulation in formation problems of unmanned vehicle swarms is presented to demonstrate the effectiveness of proposed algorithms.

关键词： Games Bit rate Costs Cost function Bandwidth Topology distributed algorithms Convergence Estimation Artificial intelligence Multiple coalition games limited communication resources bit rates coalition estimate strategies

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distributed Algorithm Over Time-Varying Unbalanced Graphs for Optimization Problem Subject to Multiple Local Constraints

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2025年第1期12卷 387-402页

作者： Liu, Hongzhe Yu, Wenwu Wen, Guanghui Zheng, Wei Xing Southeast Univ Sch Math Nanjing 210096 Peoples R China Southeast Univ Sch Math Nanjing 210096 Peoples R China Purple Mt Labs Nanjing 211111 Peoples R China Western Sydney Univ Sch Comp Data & Math Sci Sydney NSW 2751 Australia

This article addresses the optimization problem with its global objective function being composed of multiple convex functions under multiple nonidentical local constraints. The specific purpose is to resolve the studied optimization problem in a distributed manner in the presence of the time-varying unbalanced graph sequence. For this purpose, an efficient distributed discrete-time algorithm is developed over the time-varying unbalanced graph sequence by improving the classical push-pull algorithms. Moreover, for the developed distributed discrete-time algorithm, a rigorous analysis is made of its convergence property to the optimal solution as well as its convergence rate under some standard assumptions. Finally, numerical simulations are carried out to demonstrate the good performance of the designed algorithm.

关键词： Optimization Convergence Vectors Directed graphs Network systems Linear programming distributed algorithms Control systems Numerical simulation Standards distributed optimization algorithm improved push-pull framework multiple local constraints time-varying unbalanced graphs

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Robust distributed Nash Equilibrium Seeking Subject to Communication Constraints

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2025年第3期70卷 1941-1948页

作者： Liu, Lupeng Lu, Maobin Wang, Shimin Deng, Fang Chen, Jie Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China MIT Dept Chem Engn Cambridge MA 02142 USA Beijing Inst Technol Beijing 100081 Peoples R China Tongji Univ Shanghai 200092 Peoples R China

In this article, we address the robust distributed Nash equilibrium seeking problem of N-player games under switching networks and communication delays. The salient feature of this work is that the switching communication networks can be uniformly strongly connected, and the communication delays are allowed to be arbitrarily unknown, time-varying and bounded. To solve the problem, we construct a distributed estimator for each player to estimate all players' strategies through unreliable communication networks. Based on the gradient play technique, we design a distributed Nash equilibrium seeking law. Then, we obtain the closed-loop system, which is an interconnected system of a nonlinear subsystem and a linear time-delay subsystem. By constructing the Lyapunov-Krasovskii functional, and designing the controller parameter in the sense of the small gain theorem, we achieve robust Nash equilibrium seeking asymptotically in spite of unreliable communication networks. Finally, we illustrate our proposed approach by its application to practical motion control of mobile robots with an experiment.

关键词： Nash equilibrium Delays Communication networks Switches Games Vectors Cost function distributed algorithms Motion control Information exchange Non-cooperative game distributed Nash equilibrium (NE) seeking multi-agent systems robust control unreliable communication networks

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Robustness Assessment of distributed Optimal Power Flow Under Communication Non-Idealities

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2025年第2期61卷 2077-2092页

作者： Gray, Nathan Paul, Subho Dubey, Anamika Bose, Anjan Touhiduzzaman, Md. Ogle, James Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99163 USA Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99163 USA Indian Inst Technol BHU Dept Elect Engn AMRIT Res Lab Varanasi 221005 India Pacific Northwest Natl Lab Energy & Environm Directorate Richland WA 99354 USA

In recent years, distributed optimal power flow (OPF) algorithms have found applications to distribution system operations. These algorithms decompose the system into small areas, each solving a local optimization problem and periodically sharing boundary variable values with neighbors. Unlike centralized approaches, the performance of distributed algorithms is significantly affected by non-ideal communication conditions. This article assesses the performance of a fast distributed algorithm, named Equivalent Network Approximation method (ENApp), for three-phase radial distribution system under four different non-ideal communication scenarios, erroneous data transfer, packet loss, additive noise effect, and communication delays. First, the paper proposes ENApp-based distributed OPF algorithms for normal and stressed main grid conditions. Communication non-idealities are considering the physical aspects of two widely used wide-area network mediums, viz. power line communication and optical fiber. The performance is evaluated using the IEEE 123 bus test system in a cyber-physical co-simulation environment based on the Hierarchical Engine for Large-scale Infrastructure Co-Simulation (HELICS), providing insights into ENApp's robustness in terms of convergence time and success rate.

关键词： Cyber-physical systems distributed algorithms HELICS HELICS optimal power flow optimal power flow power distribution systems power distribution systems power distribution systems

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distributed online path-length-independent algorithm for noncooperative games over unbalanced digraphs☆

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AUTOMATICA 2025年 175卷

作者： Deng, Zhenhua Cent South Univ Sch Automat Changsha 410075 Peoples R China

This paper studies online noncooperative games with dynamic regrets. Existing online noncooperative games rely on the sublinear growth of the path-length of Nash equilibrium sequences when considering dynamic regrets, which implies that their cost functions cannot be rapidly time-varying. Moreover, most of related results depend on undirected communication graphs. However, in many engineering practices, the cost functions may change greatly over time and the communication graphs may be directed. Here our problem involves rapidly time-varying cost functions, i.e., the path-length of Nash equilibrium sequences at least linearly grows, and the interaction topologies are unbalanced digraphs. In order to make decisions online without regrets, we develop a distributed algorithm based on multi-step mirror descents. Under the algorithm, sublinear dynamic regret bounds are established. More importantly, the dynamic regrets are independent of the path-length of Nash equilibrium sequences, compared with existing results. Finally, the simulation results validate the effectiveness of our algorithm, and demonstrate that our algorithm has better performance than other related algorithms. (c) 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Noncooperative games Online games Nash equilibrium Multi-agent systems distributed algorithms

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