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| Main Author: | |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.02719 |
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| _version_ | 1866909378871820288 |
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| author | Qian, Sichen |
| author_facet | Qian, Sichen |
| contents | This paper investigates a fully distributed adaptive Nash equilibrium (NE) seeking algorithm for constrained noncooperative games with prescribed-time stability. On the one hand, prescribed-time stability for the proposed NE seeking algorithm is obtained by using an adaptive penalty technique, a time-varying control gain and a cosine-related time conversion function, which extends the prior asymptotic stability result. On the other hand, uncoordinated integral adaptive gains are incorporated in order to achieve the fully distribution of the algorithm. Finally, the theoretical result is validated through a numerical simulation based on a standard power market scenario. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_02719 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Fully Distributed Adaptive Nash Equilibrium Seeking Algorithm for Constrained Noncooperative Games with Prescribed Performance Qian, Sichen Optimization and Control This paper investigates a fully distributed adaptive Nash equilibrium (NE) seeking algorithm for constrained noncooperative games with prescribed-time stability. On the one hand, prescribed-time stability for the proposed NE seeking algorithm is obtained by using an adaptive penalty technique, a time-varying control gain and a cosine-related time conversion function, which extends the prior asymptotic stability result. On the other hand, uncoordinated integral adaptive gains are incorporated in order to achieve the fully distribution of the algorithm. Finally, the theoretical result is validated through a numerical simulation based on a standard power market scenario. |
| title | Fully Distributed Adaptive Nash Equilibrium Seeking Algorithm for Constrained Noncooperative Games with Prescribed Performance |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2411.02719 |