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distributed control strategy of central heating system based on multi-agent consensus

APPLIED THERMAL ENGINEERING 2025年 262卷

作者： Su, Gang Peng, Yongheng Yao, Wanxiang Zhang, Shuangyang Tianjin Chengjian Univ Sch Control & Mech Engn Tianjin 300384 Peoples R China Anhui Jianzhu Univ Anhui Prov Key Lab Intelligent Bldg Energy Saving Hefei 230022 Peoples R China Qingdao Univ Technol iSMART Qingdao 266033 Peoples R China Tianjin Jingwei Hirain Technol Ltd Tianjin 300384 Peoples R China

In this study, a centralised heat supply system based on a distributed multi-agent consistency algorithm is proposed, aiming at solving the problems of energy wastage and low quality of heat supply due to uneven heat distribution and supply-demand imbalance in the current system. By constructing a multi-agent model based on a typical first-order discrete consistency algorithm and matrix operations, the distributed coordinated control among the intelligences in the system is realised. The system is simulated under four typical operating conditions, including supply-demand equilibrium, heat shortage, demand fluctuation and communication topology change. The simulation results show that the proposed method can dynamically adjust the heat distribution under demand fluctuation, effectively reduce energy waste, and significantly improve the stability and coordination of the system. Compared with the traditional centralised control method, this distributed multi-agent system achieves higher energy efficiency and more balanced heat supply in different scenarios. The results demonstrate the potential of the multi-agent consistency algorithm in centralised heat supply systems and expand its prospects in the field of heat supply.

关键词： distributed multi-agent system District heating system Heat balance multi-agent consensus

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Age of Incorrect Information-Aware Data Dissemination for distributed multi-agent systems

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IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS 2024年第10期23卷 15705-15718页

作者： He, Guojun Zhang, Shengyu Feng, Mingjie Li, Silan Jiang, Tao Huazhong Univ Sci & Technol Res Ctr 6G Mobile Commun Sch Cyber Sci & Engn Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Wuhan Natl Lab Optoelect Wuhan 430074 Peoples R China

In this paper, we propose an age of incorrect information (AoII)-aware data dissemination scheme for distributed multi-agent systems (MASs). In the proposed scheme, AoII is utilized to measure the importance of data in terms of timeliness and content. We formulate the joint optimization of time slot allocation and agent selection as a decentralized partially observable Markov decision process (Dec-POMDP), with the objective of minimizing the AoII. To solve the Dec-POMDP, a novel multi-agent reinforcement learning algorithm (DV-MAPPO) is proposed. In particular, to tackle challenges posed by the partial observability of global system information, each agent estimates the global system state using variational inference. Moreover, to improve the accuracy of global system state estimation, each agent is given an intrinsic reward that is dominated by the accuracy of estimates. The proposed data dissemination scheme is implemented and evaluated in various missions. Simulation results show that the proposed data dissemination scheme outperforms traditional data dissemination schemes in terms of AoII. Furthermore, in typical multi-agent collaborative tasks, the proposed scheme facilitates more efficient cooperation among multiple agents compared to the data distribution mechanisms that ignore the importance of data.

关键词： Data dissemination Ad hoc networks Measurement Task analysis Optimization Wireless communication Sensors Age of incorrect information multi-agent reinforcement learning data dissemination distributed multi-agent system task-oriented communication artificial intelligence

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A Backbone-Listener Relative Localization Scheme for distributed multi-agent systems

A Backbone-Listener Relative Localization Scheme for Distrib...

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IEEE Global Communications Conference (GLOBECOM)

作者： Li, Xiaoxiang Liu, Yan Wang, Yunlong Shen, Yuan Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China China Satellite Network Innovat Co Ltd Beijing Peoples R China

ISBN: (纸本)9781665435406

Reliable and accurate localization awareness is of great importance for the distributed multi-agent system (DMAS). Instead of global information, measurements only between neighbors pose locatability and accuracy challenges for distributed systems, which leads to the development and application of relative localization. In this paper, we put forward a backbone-listener localization scheme for the D-MAS. agents switch backbone-listener modes through a node selection strategy. Position and orientation angle of agents are jointly estimated by range and angle information fusion. A distributed multi-dimensional scaling method is proposed for backbone agents to maintain the topology estimation. And listener agents ensure the localization capacity through a least square range and angle fusion algorithm. Extensive simulation and real-world experiments validate that our method achieves decimeter-level accuracy relative localization.

关键词： cooperative localization distributed multi-agent system hardware implementation

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Cloning, Resource Exchange, and Relation Adaptation: An Integrative Self-Organisation Mechanism in a distributed agent Network

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IEEE TRANSACTIONS ON PARALLEL AND distributed systemS 2014年第4期25卷 887-897页

作者： Ye, Dayong Zhang, Minjie Sutanto, Danny Univ Wollongong Fac Informat Sch Comp Sci & Software Engn Wollongong NSW 2522 Australia Univ Wollongong Fac Informat Sch Elect Comp & Telecommun Engn Wollongong NSW 2522 Australia

Self-organisation provides a suitable paradigm for developing self-managed complex distributed systems, such as grid computing and sensor networks. In this paper, an integrative self-organisation mechanism is proposed. Unlike current related studies, which propose only a single principle of self-organisation, this mechanism synthesises the three principles of self-organisation: cloning/spawning, resource exchange and relation adaptation. Based on this mechanism, an agent can autonomously generate new agents when it is overloaded, exchange resources with other agents if necessary, and modify relations with other agents to achieve a better agent network structure. In this way, agents can adapt to dynamic environments. The proposed mechanism is evaluated through a comparison with three other approaches, each of which represents state-of-the-art research in each of the three self-organisation principles. Experimental results demonstrate that the proposed mechanism outperforms the three approaches in terms of the profit of individual agents and the entire agent network, the load-balancing among agents, and the time consumption to finish a simulation run.

关键词： distributed multi-agent system self-organisation reinforcement learning

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A Decentralized Approach for Frequency Control and Economic Dispatch in Smart Grids

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IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND systemS 2017年第3期7卷 447-458页

作者： Lu, Pengpeng Zhao, Jinquan Yao, Jianguo Yang, Shengchun Hohai Univ Coll Energy & Elect Engn Nanjing 211100 Jiangsu Peoples R China China Elect Power Res Inst Power Automat Dept Nanjing 210003 Jiangsu Peoples R China

This paper proposes a decentralized approach for frequency control and economic dispatch in smart grids with distributed energy resources and responsive demands. The approach is implemented based on a distributed multi-agent system, in which each agent works in a collaborative manner via local computation and peer to peer communication. The approach is comprised of two strategies. A consensus-based strategy is implemented at the supply side to regulate system frequency economically. Self-adaptive updating rules are proposed for the key parameters to improve the accuracy and robustness of the consensus-based strategy. A threshold-based strategy is implemented at the demand side to provide ancillary services for frequency regulation. Simulation results are presented to demonstrate the effectiveness and robustness of the approach.

关键词： Decentralized approach distributed energy resources distributed multi-agent system economic dispatch frequency control responsive demands

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multi-agent job shop scheduling system based on co-operative approach of idle time minimisation

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2012年第2期50卷 409-424页

作者： Kouider, Ahmed Bouzouia, Brahim Adv Technol Dev Ctr CDTA Algiers 16303 Algeria

In this paper, a distributed multi-agent scheduling system (MASS) based on co-operative approach is proposed to solve static and dynamic job shop scheduling problems (JSSP). The proposed system is composed of two kinds of agents, Supervisor agents and Resource agents. The Supervisor agent decomposes JSSP into interrelated sub-problems and the Resource agents co-operate, through a distributed approach of local idle time minimisation, to solve this problem which is known as one of the most difficult NP-hard problems. Computational results are presented to show the efficiency of MASS in static job shop scheduling. Then, a comparison of the computational results between MASS and some common dispatching rules, on dynamic job arrivals, is studied in terms of effectiveness and stability. Finally, the developed system is validated within an illustrative example, to demonstrate the feasibility of MASS.

关键词： job shop scheduling distributed multi-agent system combinatorial optimisation

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Asynchronous Broadcast-Based Convex Optimization Over a Network

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2011年第6期56卷 1337-1351页

作者： Nedic, Angelia Univ Illinois Ind & Enterprise Syst Engn Dept Urbana IL 61801 USA

We consider a distributed multi-agent network system where each agent has its own convex objective function, which can be evaluated with stochastic errors. The problem consists of minimizing the sum of the agent functions over a commonly known constraint set, but without a central coordinator and without agents sharing the explicit form of their objectives. We propose an asynchronous broadcast-based algorithm where the communications over the network are subject to random link failures. We investigate the convergence properties of the algorithm for a diminishing (random) stepsize and a constant stepsize, where each agent chooses its own stepsize independently of the other agents. Under some standard conditions on the gradient errors, we establish almost sure convergence of the method to an optimal point for diminishing stepsize. For constant stepsize, we establish some error bounds on the expected distance from the optimal point and the expected function value. We also provide numerical results.

关键词： Asynchronous algorithms convex optimization distributed multi-agent system random broadcast network

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Dual averaging method for solving multi-agent saddle-point problems with quantized information

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TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL 2014年第1期36卷 38-46页

作者： Yuan, Deming Ma, Qian Wang, Zhen Nanjing Univ Posts & Telecommun Coll Automat Nanjing 210046 Jiangsu Peoples R China Nanjing Univ Sci & Technol Sch Automat Nanjing Jiangsu Peoples R China Shandong Univ Sci & Technol Coll Informat Sci & Engn Qingdao Shandong Peoples R China

In this paper we study the multi-agent saddle-point problems where multiple agents try to collectively optimize a sum of local convex-concave functions, each of which is available to one specific agent in the network. We propose a distributed primal-dual subgradient method under the constraint that agents can only communicate quantized information. The method can be implemented over a time-varying network while satisfying some standard connectivity conditions. We provide convergence results and convergence rate estimates for the proposed method. In particular, we provide an error bound on its convergence rate to highlight the dependence on the quantization resolution. We have also provided a numerical example to show the effectiveness of the proposed method.

关键词： distributed multi-agent system dual averaging average consensus saddle-point problems deterministic quantization

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distributed Random Projection Algorithm for Convex Optimization

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IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING 2013年第2期7卷 221-229页

作者： Lee, Soomin Nedic, Angelia Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA Univ Illinois Ind & Enterprise Syst Engn Dept Urbana IL 61801 USA

Random projection algorithm is of interest for constrained optimization when the constraint set is not known in advance or the projection operation on the whole constraint set is computationally prohibitive. This paper presents a distributed random projection algorithm for constrained convex optimization problems that can be used by multiple agents connected over a time-varying network, where each agent has its own objective function and its own constrained set. We prove that the iterates of all agents converge to the same point in the optimal set almost surely. Experiments on distributed support vector machines demonstrate good performance of the algorithm.

关键词： Asynchronous algorithms distributed convex optimization distributed multi-agent system random gossip network

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Robust distributed system of multi-Dimension Education agents

Robust Distributed System of Multi-Dimension Education Agent...

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2002 International Symposium on distributed Computing and Applications for Business Engineering and Science

作者： Tao Gong and Zixing Cai, IEEE Senior Member College of Information Science & Engineering, Central South University Changsha, Hunan 410083, China

In this paper, a novel Robust system of multi-Dimension Education agents (RSMDEA) has been proposed. RSMDEA is based on a distributed and parallel network-computing platform with multi-agent technique and distributed and parallel algorithms, such as co-evolutionary algorithms. RSMDEA can also be applied into multi-dimension education network platform or applications. distributed and parallel architecture is the important feature of RSMDEA. Another important feature of RSMDEA is robustness. Based on problem reduction method, robust problem of RSMDEA in ideal distributed environment has been reduced and transformed into robust problems of single agents and discrete control processes. RSMDEA can be used widely in E-learning fields, especially for today's education network with too many unsafe challenges.

关键词： distributed multi-agent system distributed and parallel algorithm Model on reducing robust problem Model on robustness relativity multi-dimension education system

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