Data-Driven Structured Robust Control of Linear Systems
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| _version_ | 1866910703237988352 |
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| author | Miller, Jared Eising, Jaap Dörfler, Florian Smith, Roy S. |
| author_facet | Miller, Jared Eising, Jaap Dörfler, Florian Smith, Roy S. |
| contents | Static structured control refers to the task of designing a state-feedback controller such that the control gain satisfies a subspace constraint. Structured control has applications in control of communication-inhibited dynamical systems, such as systems in networked environments. This work performs $H_2$-suboptimal regulation under a common structured state-feedback controller for a class of data-consistent plants. The certification of $H_2$-performance is attained through a combination of standard $H_2$ LMIs, convex sufficient conditions for structured control, and a matrix S-lemma for set-membership. The resulting convex optimization problems are linear matrix inequalities whose size scales independently of the number of data samples collected. Data-driven structured $H_2$-regulation control is demonstrated on example systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_11542 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Data-Driven Structured Robust Control of Linear Systems Miller, Jared Eising, Jaap Dörfler, Florian Smith, Roy S. Optimization and Control Systems and Control Static structured control refers to the task of designing a state-feedback controller such that the control gain satisfies a subspace constraint. Structured control has applications in control of communication-inhibited dynamical systems, such as systems in networked environments. This work performs $H_2$-suboptimal regulation under a common structured state-feedback controller for a class of data-consistent plants. The certification of $H_2$-performance is attained through a combination of standard $H_2$ LMIs, convex sufficient conditions for structured control, and a matrix S-lemma for set-membership. The resulting convex optimization problems are linear matrix inequalities whose size scales independently of the number of data samples collected. Data-driven structured $H_2$-regulation control is demonstrated on example systems. |
| title | Data-Driven Structured Robust Control of Linear Systems |
| topic | Optimization and Control Systems and Control |
| url | https://arxiv.org/abs/2411.11542 |