Distributed Algorithm Design for Aggregative Games of Euler-Lagrange Systems and Its Application to Smart Grids
The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the var...
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| Published in: | IEEE transactions on cybernetics Vol. 52; no. 8; pp. 8315 - 8325 |
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| Format: | Journal Article |
| Language: | English |
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United States
IEEE
01.08.2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 2168-2267, 2168-2275, 2168-2275 |
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| Abstract | The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the variational generalized Nash equilibrium (GNE) of the game. This article analyzes the convergence of two algorithms by utilizing singular perturbation analysis and variational analysis. The two algorithms exponentially and asymptotically converge to the variational GNE of the game, respectively. Moreover, the results are applied to the electricity market games of smart grids. By the algorithms, turbine-generator systems can seek the variational GNE of electricity markets autonomously. Finally, simulation examples verify the methods. |
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| AbstractList | The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the variational generalized Nash equilibrium (GNE) of the game. This article analyzes the convergence of two algorithms by utilizing singular perturbation analysis and variational analysis. The two algorithms exponentially and asymptotically converge to the variational GNE of the game, respectively. Moreover, the results are applied to the electricity market games of smart grids. By the algorithms, turbine-generator systems can seek the variational GNE of electricity markets autonomously. Finally, simulation examples verify the methods.The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the variational generalized Nash equilibrium (GNE) of the game. This article analyzes the convergence of two algorithms by utilizing singular perturbation analysis and variational analysis. The two algorithms exponentially and asymptotically converge to the variational GNE of the game, respectively. Moreover, the results are applied to the electricity market games of smart grids. By the algorithms, turbine-generator systems can seek the variational GNE of electricity markets autonomously. Finally, simulation examples verify the methods. The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics. On the strength of gradient descent, state feedback, and dynamic average consensus, two distributed algorithms are developed to seek the variational generalized Nash equilibrium (GNE) of the game. This article analyzes the convergence of two algorithms by utilizing singular perturbation analysis and variational analysis. The two algorithms exponentially and asymptotically converge to the variational GNE of the game, respectively. Moreover, the results are applied to the electricity market games of smart grids. By the algorithms, turbine-generator systems can seek the variational GNE of electricity markets autonomously. Finally, simulation examples verify the methods. |
| Author | Deng, Zhenhua |
| Author_xml | – sequence: 1 givenname: Zhenhua orcidid: 0000-0001-7225-5238 surname: Deng fullname: Deng, Zhenhua email: zhdeng@amss.ac.cn organization: School of Automation, Central South University, Changsha, China |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33531313$$D View this record in MEDLINE/PubMed |
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| Snippet | The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler-Lagrange (EL) dynamics.... The aggregative games are addressed in this article, in which there are coupling constraints among decisions and the players have Euler–Lagrange (EL) dynamics.... |
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| SubjectTerms | Aggregative games Algorithms Communication networks Convergence Couplings cyber-physical systems (CPSs) Distributed algorithms Electricity Electricity supply industry Euler–Lagrange systems Game theory Games generalized Nash equilibrium (GNE) Heuristic algorithms multiagent systems Perturbation methods Singular perturbation Smart grid Smart grids State feedback Turbines |
| Title | Distributed Algorithm Design for Aggregative Games of Euler-Lagrange Systems and Its Application to Smart Grids |
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