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| Main Authors: | , |
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| Format: | Preprint |
| Published: |
2024
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2409.02350 |
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| _version_ | 1866914935174332416 |
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| author | Mariano, Simone Cantoni, Michael |
| author_facet | Mariano, Simone Cantoni, Michael |
| contents | The main result relates to structured robust stability analysis of an input-output model for networks with link uncertainty. It constitutes a collection of integral quadratic constraints, which together imply robust stability of the uncertain networked dynamics. Each condition is decentralized in the sense that it depends on model data pertaining to the neighbourhood of a specific agent. By contrast, pre-existing conditions for the network model are link-wise decentralized, with each involving conservatively more localized problem data. A numerical example is presented to illustrate the advantage of the new broader neighbourhood conditions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2409_02350 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Neighbourhood conditions for network stability with link uncertainty Mariano, Simone Cantoni, Michael Systems and Control Dynamical Systems The main result relates to structured robust stability analysis of an input-output model for networks with link uncertainty. It constitutes a collection of integral quadratic constraints, which together imply robust stability of the uncertain networked dynamics. Each condition is decentralized in the sense that it depends on model data pertaining to the neighbourhood of a specific agent. By contrast, pre-existing conditions for the network model are link-wise decentralized, with each involving conservatively more localized problem data. A numerical example is presented to illustrate the advantage of the new broader neighbourhood conditions. |
| title | Neighbourhood conditions for network stability with link uncertainty |
| topic | Systems and Control Dynamical Systems |
| url | https://arxiv.org/abs/2409.02350 |