Gradient Free Cooperative Seeking of a Moving Source
Fuente:
arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2022
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866912207637315584 |
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| author | Michael, Elad Manzie, Chris Wood, Tony A. Zelazo, Daniel Shames, Iman |
| author_facet | Michael, Elad Manzie, Chris Wood, Tony A. Zelazo, Daniel Shames, Iman |
| contents | In this paper, we consider the optimisation of a time varying scalar field by a network of agents with no gradient information. We propose a composite control law, blending extremum seeking with formation control in order to converge to the extrema faster by minimising the gradient estimation error. By formalising the relationship between the formation and the gradient estimation error, we provide a novel analysis to prove the convergence of the network to a bounded neighbourhood of the field's time varying extrema. We assume the time-varying field satisfies the Polyak Lojasiewicz inequality and the gradient is Lipschitz continuous at each iteration. Numerical studies and comparisons are provided to support the theoretical results. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2201_00446 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Gradient Free Cooperative Seeking of a Moving Source Michael, Elad Manzie, Chris Wood, Tony A. Zelazo, Daniel Shames, Iman Optimization and Control In this paper, we consider the optimisation of a time varying scalar field by a network of agents with no gradient information. We propose a composite control law, blending extremum seeking with formation control in order to converge to the extrema faster by minimising the gradient estimation error. By formalising the relationship between the formation and the gradient estimation error, we provide a novel analysis to prove the convergence of the network to a bounded neighbourhood of the field's time varying extrema. We assume the time-varying field satisfies the Polyak Lojasiewicz inequality and the gradient is Lipschitz continuous at each iteration. Numerical studies and comparisons are provided to support the theoretical results. |
| title | Gradient Free Cooperative Seeking of a Moving Source |
| topic | Optimization and Control |
| url | https://arxiv.org/abs/2201.00446 |