Distributed Nash equilibrium seeking for uncertain linear multi‐agent systems by output feedback integral control.
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| Title: | Distributed Nash equilibrium seeking for uncertain linear multi‐agent systems by output feedback integral control. |
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| Authors: | Zheng, Xianxian1 (AUTHOR), Wei, Lan2 (AUTHOR), Yi, Peng3,4,5,6 (AUTHOR), Tang, Yutao1 (AUTHOR) yttang@bupt.edu.cn |
| Source: | Asian Journal of Control. May2026, Vol. 28 Issue 3, p1318-1325. 8p. |
| Subjects: | Nash equilibrium, Multiagent systems, Nash, John F., 1928-2015, Control theory (Engineering), Noncooperative games (Mathematics), Linear dynamical systems, Observability (Control theory), Feedback control systems |
| Abstract: | This paper is focused on the Nash equilibrium seeking problem for a group of high‐order dynamic players. Each player possesses a general linear dynamic with parameter uncertainties. To solve this problem, we first introduce a virtual reference generator for each player by virtue of the embedded design approach and then constructively propose an observer‐based output feedback integral controller relying on local information and computation. The decision outputs of all players are rigorously proven to reach the expected Nash equilibrium of the corresponding noncooperative game irrespective of the model uncertainties. We also give a simulation example to illustrate the effectiveness of our algorithms. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | This paper is focused on the Nash equilibrium seeking problem for a group of high‐order dynamic players. Each player possesses a general linear dynamic with parameter uncertainties. To solve this problem, we first introduce a virtual reference generator for each player by virtue of the embedded design approach and then constructively propose an observer‐based output feedback integral controller relying on local information and computation. The decision outputs of all players are rigorously proven to reach the expected Nash equilibrium of the corresponding noncooperative game irrespective of the model uncertainties. We also give a simulation example to illustrate the effectiveness of our algorithms. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 15618625 |
| DOI: | 10.1002/asjc.3739 |
