Distributed Least Squares Algorithms for Achieving Linear and Nonlinear Conservation Constraints

Yi Huang; Fengming Han

doi:10.1007/978-981-19-6226-4_87

Distributed Least Squares Algorithms for Achieving Linear and Nonlinear Conservation Constraints

Yi Huang^*, Fengming Han

^*Corresponding author for this work

School of Automation

Yangzhou Academy of Collaboration and Innovation Company Ltd.

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

Abstract

This paper proposes distributed least squares (LS) algorithms to achieve the conservation constraint via multi-agent network. In particular, the conservation constraint is that the sum of all the local functions equals to a constant. We first consider the linear conservation constraint, where each local function is linear. Then, a distributed LS algorithm is developed, which guarantees that all the agents’ states converge exponentially to a LS solution of the conservation constraint. Secondly, we further consider the nonlinear conservation constraint that is summed of multiple local nonlinear functions. By using the dynamic average tracking method, we develop an alternative distributed algorithm such that a LS solution of the nonlinear conservation constraint can be obtained. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed algorithms.

Original language	English
Title of host publication	Proceedings of 2022 Chinese Intelligent Systems Conference - Volume II
Editors	Yingmin Jia, Weicun Zhang, Yongling Fu, Shoujun Zhao
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	913-921
Number of pages	9
ISBN (Print)	9789811962257
DOIs	https://doi.org/10.1007/978-981-19-6226-4_87
Publication status	Published - 2022
Event	18th Chinese Intelligent Systems Conference, CISC 2022 - Beijing, China Duration: 15 Oct 2022 → 16 Oct 2022

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	951 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	18th Chinese Intelligent Systems Conference, CISC 2022
Country/Territory	China
City	Beijing
Period	15/10/22 → 16/10/22

Keywords

Conservation constraint
Distributed algorithms
Least squares solution
Multi-agent networks

Access to Document

10.1007/978-981-19-6226-4_87

Cite this

Huang, Y., & Han, F. (2022). Distributed Least Squares Algorithms for Achieving Linear and Nonlinear Conservation Constraints. In Y. Jia, W. Zhang, Y. Fu, & S. Zhao (Eds.), Proceedings of 2022 Chinese Intelligent Systems Conference - Volume II (pp. 913-921). (Lecture Notes in Electrical Engineering; Vol. 951 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-6226-4_87

Huang, Yi ; Han, Fengming. / Distributed Least Squares Algorithms for Achieving Linear and Nonlinear Conservation Constraints. Proceedings of 2022 Chinese Intelligent Systems Conference - Volume II. editor / Yingmin Jia ; Weicun Zhang ; Yongling Fu ; Shoujun Zhao. Springer Science and Business Media Deutschland GmbH, 2022. pp. 913-921 (Lecture Notes in Electrical Engineering).

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title = "Distributed Least Squares Algorithms for Achieving Linear and Nonlinear Conservation Constraints",

abstract = "This paper proposes distributed least squares (LS) algorithms to achieve the conservation constraint via multi-agent network. In particular, the conservation constraint is that the sum of all the local functions equals to a constant. We first consider the linear conservation constraint, where each local function is linear. Then, a distributed LS algorithm is developed, which guarantees that all the agents{\textquoteright} states converge exponentially to a LS solution of the conservation constraint. Secondly, we further consider the nonlinear conservation constraint that is summed of multiple local nonlinear functions. By using the dynamic average tracking method, we develop an alternative distributed algorithm such that a LS solution of the nonlinear conservation constraint can be obtained. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed algorithms.",

keywords = "Conservation constraint, Distributed algorithms, Least squares solution, Multi-agent networks",

author = "Yi Huang and Fengming Han",

note = "Publisher Copyright: {\textcopyright} 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 18th Chinese Intelligent Systems Conference, CISC 2022 ; Conference date: 15-10-2022 Through 16-10-2022",

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Huang, Y & Han, F 2022, Distributed Least Squares Algorithms for Achieving Linear and Nonlinear Conservation Constraints. in Y Jia, W Zhang, Y Fu & S Zhao (eds), Proceedings of 2022 Chinese Intelligent Systems Conference - Volume II. Lecture Notes in Electrical Engineering, vol. 951 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 913-921, 18th Chinese Intelligent Systems Conference, CISC 2022, Beijing, China, 15/10/22. https://doi.org/10.1007/978-981-19-6226-4_87

Distributed Least Squares Algorithms for Achieving Linear and Nonlinear Conservation Constraints. / Huang, Yi; Han, Fengming.
Proceedings of 2022 Chinese Intelligent Systems Conference - Volume II. ed. / Yingmin Jia; Weicun Zhang; Yongling Fu; Shoujun Zhao. Springer Science and Business Media Deutschland GmbH, 2022. p. 913-921 (Lecture Notes in Electrical Engineering; Vol. 951 LNEE).

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

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AB - This paper proposes distributed least squares (LS) algorithms to achieve the conservation constraint via multi-agent network. In particular, the conservation constraint is that the sum of all the local functions equals to a constant. We first consider the linear conservation constraint, where each local function is linear. Then, a distributed LS algorithm is developed, which guarantees that all the agents’ states converge exponentially to a LS solution of the conservation constraint. Secondly, we further consider the nonlinear conservation constraint that is summed of multiple local nonlinear functions. By using the dynamic average tracking method, we develop an alternative distributed algorithm such that a LS solution of the nonlinear conservation constraint can be obtained. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed algorithms.

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Huang Y, Han F. Distributed Least Squares Algorithms for Achieving Linear and Nonlinear Conservation Constraints. In Jia Y, Zhang W, Fu Y, Zhao S, editors, Proceedings of 2022 Chinese Intelligent Systems Conference - Volume II. Springer Science and Business Media Deutschland GmbH. 2022. p. 913-921. (Lecture Notes in Electrical Engineering). doi: 10.1007/978-981-19-6226-4_87