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检索条件"主题词=distributed algorithms"

共 6237 条记录，以下是731-740 订阅

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distributed Nonconvex L2 - L∞ Containment Control for Multi-Agent Systems

Distributed Nonconvex L2 - L∞ Containment Control for Multi...

引用

IEEE 17th International Conference on Control and Automation (ICCA)

作者： Hu, Yangming Xu, Jiahao

ISBN: (数字)9781665495721

ISBN: (纸本)9781665495721

In this paper, we investigate the nonconvex L-2 - L-infinity containment control. The objective is to use local information to make all followers move to the convex hull formed by multiple stationary leaders while satisfying a desired L-2 - L-infinity performance index and the control input of each follower remain in their corresponding constraint set. Based on constraint operator and Lyapunov function, some sufficient condition are given to solve nonconvex L-2 - L-infinity containment control problem.

关键词： Sufficient conditions Automation Control systems Trajectory Performance analysis distributed algorithms Multi-agent systems

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distributed Economic Dispatch in a Microgrid Using Proportional-Integral Consensus

Distributed Economic Dispatch in a Microgrid Using Proportio...

引用

IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)

作者： Naina P M K. Shanti Swarup Department of Electrical Engineering IIT Madras

ISBN: (数字)9798350373929

ISBN: (纸本)9798350373936

With the increasing penetration of distributed generators, distributed algorithms have become essential for efficient power system operations. However, these algorithms are often vulnerable to noise and communication delays due to their dependence on communication infrastructures. A consensus-based decentralized method is presented in this paper to solve economic dispatch in microgrids, accounting for practical communication challenges such as dynamically switching topologies, communication delays, and noise. A proportional-integral (PI) consensus protocol is proposed to address these issues, which includes an integral term to mitigate the harmful effects of noise and delays. The multi-agent system (MAS) model is used to describe the microgrid. A distributed PI consensus approach with two primary consensus variables—the global power imbalance (∆P ) and the incremental cost (λ)—is employed to solve the economic dispatch problem. A key benefit of this method is that it allows generating units to maintain the confidentiality of their cost characteristics. The effectiveness of the presented approach is demonstrated by simulation results on a microgrid with five buses.

关键词： Costs Noise Asia Microgrids Switches Delays Smart grids Consensus protocol Topology distributed algorithms

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distributed Regularization-Based Nash Equilibrium Seeking for Merely Monotone Games Under Directed Graphs: A Prescribed-Time Approach

Distributed Regularization-Based Nash Equilibrium Seeking fo...

引用

Annual Conference of Industrial Electronics Society

作者： Jinyang Rui Lei Ding Institute of Advanced Technology for Carbon Neutrality Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9781665464543

ISBN: (纸本)9781665464550

In this paper, we consider the prescribed-time distributed Nash equilibrium (PTDNE) seeking problem in noncooperative monotone games under directed graphs. For the purpose of compensating for the absence of strong monotoncity condition, a time-varying decay regularization term is implemented in the merely monotone game. By using the regularization scheme, a new prescribed-time distributed algorithm is established for seeking the least-norm Nash equilibrium in monotone games, where the leader-following consensus protocol and gradient play are incorporated. Based on the proposed strategies, some sufficient conditions on time-varying parameters are provided through Lyapunov function analysis, under which the players’ actions are capable of converging to the least-norm one of the Nash equilibria in a prescribed time. Finally, numerical simulations on a network of players demonstrate the benefits of the proposed algorithm in achieving convergence at any arbitrary time.

关键词： Industrial electronics Sufficient conditions Gradient methods Quantization (signal) Directed graphs Games Nash equilibrium Numerical simulation distributed algorithms Lyapunov methods

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DACA: A distributed Algorithm for Task Partitioning and Offloading in Mobile Edge Computing Networks Supporting Transformer

DACA: A Distributed Algorithm for Task Partitioning and Offl...

引用

Smart World Congress (SWC), IEEE

作者： Yehan Deng Jingjing Li Na Tang School of Computer South China Normal University Guangzhou China

ISBN: (数字)9798331520861

ISBN: (纸本)9798331520878

Recent studies have explored collaborative Transformer-based inference in edge computing (EC), but they often overlook the mobility of users and edge devices, leading to potential reliability issues. This paper aims to minimize inference latency in mobile edge computing (MEC) by considering heterogeneity in mobility, computation, and communication. We propose a task partitioning model utilizing the GPipe scheme for Transformer-based inference. The task partitioning and offloading problem is then formulated with constraints on computation resources and mobility, decomposed into a bin-packing problem and an integer optimization problem. To solve these subproblems, we introduce the distributed Aggregated Competition Algorithm (DACA). Extensive simulations and testbed experiments demonstrate the high performance of our proposed algorithm in minimizing inference latency across heterogeneous mobile edge devices and networks.

关键词： Performance evaluation Multi-access edge computing Computational modeling Simulation Transformers Inference algorithms Partitioning algorithms Reliability distributed algorithms Optimization

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A distributed Algorithm for Coordination in Energy Communities *

A Distributed Algorithm for Coordination in Energy Communiti...

引用

IEEE International Conference on Automation Science and Engineering (CASE)

作者： Riccardo Brumali Guido Carnevale Ruggero Carli Giuseppe Notarstefano Department of Electrical Electronic and Information Engineering University of Bologna Bologna Italy Department of Information Engineering University of Padova Padova Italy

ISBN: (数字)9798350358513

ISBN: (纸本)9798350358520

In this paper, we consider an energy trading problem in a network of interconnected MicroGrids. We consider a model in which each unit can produce, consume, or store energy and is classified as a seller or buyer, depending on its energy status. Indeed, the sellers have an excess of energy to be sold or stored, while the buyers, instead, need to buy energy from the other units or the main grid to satisfy their energy demand. In this setting, we formulate a cooperative optimization problem with the aim of finding the best tradeoff between the competitive objectives of (i) maximizing the sellers’ revenue, (ii) ensuring storage, (iii) minimizing the buyers’ energy cost, and (iv) satisfying the energy demand. Then, we recast the obtained problem in the so-called aggregative optimization scenario, a recently emerged framework in which a network of agents aims at cooperatively minimizing the sum of local functions each depending on both global (the so-called aggregative variable) and local quantities. Hence, we propose a distributed scheme tailored for aggregative optimization. The numerical simulations confirm the effectiveness of our approach showing the convergence of the chosen distributed algorithm to a stationary point of the problem. Finally, we test the flexibility of the model by considering scenarios where agents have different preferences.

关键词： Energy consumption Costs Microgrids Games Numerical simulation Numerical models distributed algorithms Optimization Convergence Testing

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Fully distributed EV Charging Scheduling for Load Flattening in V2G Systems

Fully Distributed EV Charging Scheduling for Load Flattening...

引用

IEEE Conference on Decision and Control

作者： Jinwook Heo Soojeong Hyeon Hyungbo Shim Jinsung Kim Department of Electrical and Computer Engineering ASRI Seoul National University Seoul Korea Vehicle SW Division Hyundai Motor Company Hwaseong Korea

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper presents a fully distributed algorithm for scheduling electric vehicle (EV) charging and discharging to flatten the total load of the grid, while considering constraints on grid transmission capacity. As a fully distributed solution, the proposed algorithm operates without the need for a central unit. Instead, each agent only communicates a single dual variable with its neighboring agents based on a communication graph, and thus no private information is shared. In particular, the algorithm does not rely on initial conditions, ensuring robustness in online changes of operational conditions. Simulation results verify the effectiveness of the proposed algorithm.

关键词： Vehicle-to-grid Privacy Scheduling algorithms Heuristic algorithms Simulation Scheduling Electric vehicle charging Robustness Vehicle dynamics distributed algorithms

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Spatio-Temporal Communication Compression in distributed Prime-Dual Flows

Spatio-Temporal Communication Compression in Distributed Pri...

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IEEE Conference on Decision and Control

作者： Zihao Ren Lei Wang Deming Yuan Hongye Su Guodong Shi College of Control Science and Engineering Zhejiang University P.R. China School of Automation Nanjing University of Science and Technology P.R. China Australia Centre for Field Robotics University of Sydney Australia

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we study distributed prime-dual flows for multi-agent optimization with spatio-temporal compressions. The central aim of multi-agent optimization is for a network of agents to collaboratively solve a system-level optimization problem with local objective functions and node-to-node communication by distributed algorithms. The scalability of such algorithms crucially depends on the complexity of the communication messages, and a number of communication compressors for distributed optimization have recently been proposed in the literature. First of all, we introduce a general spatio-temporal compressor characterized by the stability of the resulting dynamical system along the vector field of the compressor. We show that several important distributed optimization compressors such as the greedy sparsifier, the uniform quantizer, and the scalarizer all fall into the category of this spatio-temporal compressor. Next, we propose two distributed prime-dual flows with the spatio-temporal compressors being applied to local node states and local error states, respectively, and prove (exponential) convergence of the node trajectories to the global optimizer for (strongly) convex cost functions. Finally, a few numerical examples are present to illustrate our theoretical results.

关键词： Scalability Heuristic algorithms Linear programming Compressors Vectors Trajectory Dynamical systems distributed algorithms Optimization Numerical stability

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An Economic Dispatch Method for Power System Based on distributed Mutual-Fed-Consensus

An Economic Dispatch Method for Power System Based on Distri...

引用

International Conference on Advanced Mechatronic Systems (ICAMechS)

作者： Xiangjun Li Panpan Zhang Bo Li National Key Laboratory of Renewable Energy Grid-Integration Energy Storage and Electrical Engineering Department China Electric Power Research Institute Beijing China School of Automation Engineering Northeast Electric Power University China

ISBN: (数字)9798350366204

ISBN: (纸本)9798350366211

This paper presents a distributed algorithm based on mutual feedback mechanism for economic dispatch problem of power system. In such a mutual feedback mechanism, the average of the load demand and power generated are estimated, respectively. Simulation results on standard test cases show the convergence and effectiveness of the proposed algorithm.

关键词： Economics Mechatronics Simulation Numerical simulation Generators Power systems distributed algorithms Standards Power generation Convergence

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A Robust distributed Nash Equilibrium Seeking Algorithm for Aggregative Games Under Byzantine Attacks

A Robust Distributed Nash Equilibrium Seeking Algorithm for ...

引用

American Control Conference (ACC)

作者： Jishu Zhao Peng Yi Department of Control Science and Engineering Tongji University Shanghai China Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

This paper investigates the Nash equilibrium seeking problem for aggregative games, where some players are under Byzantine attacks. Since the previous distributed algorithms might be seriously affected by Byzantine attacks that inject malicious information to the system, we propose a resilient distributed geometric-median based method to improve the robustness of the algorithm. When less than half of the players are Byzantine attackers and under strongly monotone assumption on the pseudo-gradient mapping, we show that the algorithm converges linearly to a neighborhood of the Nash Equilibrium with an error bound related to the ratio of Byzantine attackers. Finally, numerical examples are implemented to demonstrate the robustness of the proposed algorithm under various types of Byzantine attacks.

关键词： Games Nash equilibrium Robustness distributed algorithms

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distributed Average Consensus in Open Multi-Agent Systems

Distributed Average Consensus in Open Multi-Agent Systems

引用

IEEE Conference on Decision and Control

作者： Christoforos N. Hadjicostis Alejandro D. Domínguez-García Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL USA

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we consider the problem of distributed average consensus in multi-agent systems, where each agent can come in or move out of the system, possibly multiple times. In the literature, such systems are referred to as open multi-agent systems. A typical goal in such settings is to use an iterative distributed algorithm to calculate the average of some quantities of interest each agent possesses, which can be crucial in many estimation, control, or optimization applications. We consider an open multi-agent setting and propose a distributed algorithm that allows the participating agents to track their average. More specifically, if the set of agents remaining in the computation eventually settles to a certain subset of agents, then the proposed algorithm allows them (under some mild connectivity conditions) to asymptotically reach consensus to the average of the quantities of interest these remaining agents hold. Analysis and numerical examples to illustrate the operation of the proposed algorithm are also provided.

关键词： Estimation Iterative algorithms distributed algorithms Optimization Multi-agent systems

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