Distributionally robust LMI synthesis for LTI systems
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915533413154816 |
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| author | Gramlich, Dennis Yan, Shuhao Scherer, Carsten W. Ebenbauer%, Christian |
| author_facet | Gramlich, Dennis Yan, Shuhao Scherer, Carsten W. Ebenbauer%, Christian |
| contents | This article shows that distributionally robust controller synthesis as investigated in \cite{taskesen2024distributionally} can be formulated as a convex linear matrix inequality (LMI) synthesis problem. To this end, we rely on well-established convexification techniques from robust control. The LMI synthesis problem we propose has the advantage that it can be solved efficiently using off-the-shelf semi-definite programming (SDP) solvers. In addition, our formulation exposes the studied distributionally robust controller synthesis problem as an instance of robust $H_2$ synthesis. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2509_23493 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Distributionally robust LMI synthesis for LTI systems Gramlich, Dennis Yan, Shuhao Scherer, Carsten W. Ebenbauer%, Christian Optimization and Control Systems and Control This article shows that distributionally robust controller synthesis as investigated in \cite{taskesen2024distributionally} can be formulated as a convex linear matrix inequality (LMI) synthesis problem. To this end, we rely on well-established convexification techniques from robust control. The LMI synthesis problem we propose has the advantage that it can be solved efficiently using off-the-shelf semi-definite programming (SDP) solvers. In addition, our formulation exposes the studied distributionally robust controller synthesis problem as an instance of robust $H_2$ synthesis. |
| title | Distributionally robust LMI synthesis for LTI systems |
| topic | Optimization and Control Systems and Control |
| url | https://arxiv.org/abs/2509.23493 |