{"ID":2864862,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.23493","arxiv_id":"2509.23493","title":"Distributionally robust LMI synthesis for LTI systems","abstract":"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.","short_abstract":"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 w...","url_abs":"https://arxiv.org/abs/2509.23493","url_pdf":"https://arxiv.org/pdf/2509.23493v2","authors":"[\"Dennis Gramlich\",\"Shuhao Yan\",\"Carsten W. Scherer\",\"Christian Ebenbauer%\"]","published":"2025-09-27T20:50:56Z","proceeding":"math.OC","tasks":"[\"math.OC\",\"eess.SY\"]","methods":"[]","has_code":false}