Distributed Continuous-time Resource Allocation with Time-varying Resources under Quadratic Cost Functions

Lu Bai; Chao Sun; Zhi Feng; Guoqiang Hu

doi:10.1109/CDC.2018.8619295

Distributed Continuous-time Resource Allocation with Time-varying Resources under Quadratic Cost Functions

Lu Bai
, Chao Sun
, Zhi Feng
, Guoqiang Hu

Nanyang Technological University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

35 Scopus citations

Abstract

We developed distributed continuous-time algorithms to solve the resource allocation problem with quadratic cost functions and continuously time-varying resources. Since the resources are time-varying, the optimal solution is changing over time. The allocation decision variable should not only find but also track the optimal solution trajectory. In a distributed manner, the agents work collaboratively to find as well as track the optimal solution using local information. Without the local allocation feasibility constraints, a distributed algorithm is designed based on sign function and consensus protocols. The tracking error is proven to vanish in finite time. When the local allocation feasibility constraints are considered, a distributed algorithm based on singular perturbation theory and penalty function is developed. The tracking error is proven to be uniformly ultimately bounded.

Original language	English
Title of host publication	2018 IEEE Conference on Decision and Control, CDC 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	823-828
Number of pages	6
ISBN (Electronic)	9781538613955
DOIs	https://doi.org/10.1109/CDC.2018.8619295
State	Published - 2 Jul 2018
Externally published	Yes
Event	57th IEEE Conference on Decision and Control, CDC 2018 - Miami, United States Duration: 17 Dec 2018 → 19 Dec 2018

Publication series

Name	Proceedings of the IEEE Conference on Decision and Control
Volume	2018-December
ISSN (Print)	0743-1546
ISSN (Electronic)	2576-2370

Conference

Conference	57th IEEE Conference on Decision and Control, CDC 2018
Country/Territory	United States
City	Miami
Period	17/12/18 → 19/12/18

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10.1109/CDC.2018.8619295

Cite this

Bai, L., Sun, C., Feng, Z., & Hu, G. (2018). Distributed Continuous-time Resource Allocation with Time-varying Resources under Quadratic Cost Functions. In 2018 IEEE Conference on Decision and Control, CDC 2018 (pp. 823-828). Article 8619295 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2018-December). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CDC.2018.8619295

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title = "Distributed Continuous-time Resource Allocation with Time-varying Resources under Quadratic Cost Functions",

abstract = "We developed distributed continuous-time algorithms to solve the resource allocation problem with quadratic cost functions and continuously time-varying resources. Since the resources are time-varying, the optimal solution is changing over time. The allocation decision variable should not only find but also track the optimal solution trajectory. In a distributed manner, the agents work collaboratively to find as well as track the optimal solution using local information. Without the local allocation feasibility constraints, a distributed algorithm is designed based on sign function and consensus protocols. The tracking error is proven to vanish in finite time. When the local allocation feasibility constraints are considered, a distributed algorithm based on singular perturbation theory and penalty function is developed. The tracking error is proven to be uniformly ultimately bounded.",

author = "Lu Bai and Chao Sun and Zhi Feng and Guoqiang Hu",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 57th IEEE Conference on Decision and Control, CDC 2018 ; Conference date: 17-12-2018 Through 19-12-2018",

year = "2018",

month = jul,

day = "2",

doi = "10.1109/CDC.2018.8619295",

language = "英语",

series = "Proceedings of the IEEE Conference on Decision and Control",

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Bai, L, Sun, C, Feng, Z & Hu, G 2018, Distributed Continuous-time Resource Allocation with Time-varying Resources under Quadratic Cost Functions. in 2018 IEEE Conference on Decision and Control, CDC 2018., 8619295, Proceedings of the IEEE Conference on Decision and Control, vol. 2018-December, Institute of Electrical and Electronics Engineers Inc., pp. 823-828, 57th IEEE Conference on Decision and Control, CDC 2018, Miami, United States, 17/12/18. https://doi.org/10.1109/CDC.2018.8619295

Distributed Continuous-time Resource Allocation with Time-varying Resources under Quadratic Cost Functions. / Bai, Lu; Sun, Chao; Feng, Zhi et al.
2018 IEEE Conference on Decision and Control, CDC 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 823-828 8619295 (Proceedings of the IEEE Conference on Decision and Control; Vol. 2018-December).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - We developed distributed continuous-time algorithms to solve the resource allocation problem with quadratic cost functions and continuously time-varying resources. Since the resources are time-varying, the optimal solution is changing over time. The allocation decision variable should not only find but also track the optimal solution trajectory. In a distributed manner, the agents work collaboratively to find as well as track the optimal solution using local information. Without the local allocation feasibility constraints, a distributed algorithm is designed based on sign function and consensus protocols. The tracking error is proven to vanish in finite time. When the local allocation feasibility constraints are considered, a distributed algorithm based on singular perturbation theory and penalty function is developed. The tracking error is proven to be uniformly ultimately bounded.

AB - We developed distributed continuous-time algorithms to solve the resource allocation problem with quadratic cost functions and continuously time-varying resources. Since the resources are time-varying, the optimal solution is changing over time. The allocation decision variable should not only find but also track the optimal solution trajectory. In a distributed manner, the agents work collaboratively to find as well as track the optimal solution using local information. Without the local allocation feasibility constraints, a distributed algorithm is designed based on sign function and consensus protocols. The tracking error is proven to vanish in finite time. When the local allocation feasibility constraints are considered, a distributed algorithm based on singular perturbation theory and penalty function is developed. The tracking error is proven to be uniformly ultimately bounded.

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ER -

Distributed Continuous-time Resource Allocation with Time-varying Resources under Quadratic Cost Functions

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