Distributed Optimal Resource Allocation in Prescribed-Time with Time-Varying Cost Functions

Xiaohui Deng; Yongfang Liu; Yu Zhao; Dan Liu; Zhongkui Li

doi:10.1109/YAC66630.2025.11149718

Distributed Optimal Resource Allocation in Prescribed-Time with Time-Varying Cost Functions

Xiaohui Deng
, Yongfang Liu
, Yu Zhao
, Dan Liu
, Zhongkui Li

自动化学院

Northwestern Polytechnical University Xian
China Aerospace Science and Technology Corporation
Peking University

科研成果: 期刊稿件 › 会议文章 › 同行评审

摘要

In this paper, we address time-varying resource allocation problems with heterogeneous Hessian matrices across agents. A novel prescribed-time convergent algorithm is proposed by integrating distributed average consensus estimators and a prediction-correction method. The global convergence is rigorously established via Lyapunov analysis. Numerical simulations on a battery energy storage system demonstrate the algorithm's effectiveness in achieving optimal resource allocation within user-defined time horizons.

源语言	英语
页（从-至）	37-41
页数	5
期刊	Youth Academic Annual Conference of Chinese Association of Automation, YAC
期	2025
DOI	https://doi.org/10.1109/YAC66630.2025.11149718
出版状态	已出版 - 2025
活动	40th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2025 - Zhengzhou, 中国期限: 17 5月 2025 → 19 5月 2025

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10.1109/YAC66630.2025.11149718

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title = "Distributed Optimal Resource Allocation in Prescribed-Time with Time-Varying Cost Functions",

abstract = "In this paper, we address time-varying resource allocation problems with heterogeneous Hessian matrices across agents. A novel prescribed-time convergent algorithm is proposed by integrating distributed average consensus estimators and a prediction-correction method. The global convergence is rigorously established via Lyapunov analysis. Numerical simulations on a battery energy storage system demonstrate the algorithm's effectiveness in achieving optimal resource allocation within user-defined time horizons.",

keywords = "Distributed resource allocation, Prescribed-time convergence",

author = "Xiaohui Deng and Yongfang Liu and Yu Zhao and Dan Liu and Zhongkui Li",

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T1 - Distributed Optimal Resource Allocation in Prescribed-Time with Time-Varying Cost Functions

AU - Deng, Xiaohui

AU - Liu, Yongfang

AU - Zhao, Yu

AU - Liu, Dan

AU - Li, Zhongkui

PY - 2025

Y1 - 2025

N2 - In this paper, we address time-varying resource allocation problems with heterogeneous Hessian matrices across agents. A novel prescribed-time convergent algorithm is proposed by integrating distributed average consensus estimators and a prediction-correction method. The global convergence is rigorously established via Lyapunov analysis. Numerical simulations on a battery energy storage system demonstrate the algorithm's effectiveness in achieving optimal resource allocation within user-defined time horizons.

AB - In this paper, we address time-varying resource allocation problems with heterogeneous Hessian matrices across agents. A novel prescribed-time convergent algorithm is proposed by integrating distributed average consensus estimators and a prediction-correction method. The global convergence is rigorously established via Lyapunov analysis. Numerical simulations on a battery energy storage system demonstrate the algorithm's effectiveness in achieving optimal resource allocation within user-defined time horizons.

KW - Distributed resource allocation

KW - Prescribed-time convergence

UR - https://www.scopus.com/pages/publications/105030922453

U2 - 10.1109/YAC66630.2025.11149718

DO - 10.1109/YAC66630.2025.11149718

M3 - 会议文章

AN - SCOPUS:105030922453

SN - 2837-8598

SP - 37

EP - 41

JO - Youth Academic Annual Conference of Chinese Association of Automation, YAC

JF - Youth Academic Annual Conference of Chinese Association of Automation, YAC

IS - 2025

T2 - 40th Youth Academic Annual Conference of Chinese Association of Automation, YAC 2025

Y2 - 17 May 2025 through 19 May 2025

ER -

Distributed Optimal Resource Allocation in Prescribed-Time with Time-Varying Cost Functions

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