{"ID":2831229,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.08667","arxiv_id":"2512.08667","title":"Direct transfer of optimized controllers to similar systems using dimensionless MPC","abstract":"Scaled model experiments are commonly used in various engineering fields to reduce experimentation costs and overcome constraints associated with full-scale systems. The relevance of such experiments relies on dimensional analysis and the principle of dynamic similarity. However, transferring controllers to full-scale systems often requires additional tuning. In this paper, we propose a method to enable a direct controller transfer using dimensionless model predictive control, tuned automatically for closed-loop performance. With this reformulation, the closed-loop behavior of an optimized controller transfers directly to a new, dynamically similar system. Additionally, the dimensionless formulation allows for the use of data from systems of different scales during parameter optimization. We demonstrate the method on a cartpole swing-up and a car racing problem, applying either reinforcement learning or Bayesian optimization for tuning the controller parameters. Software used to obtain the results in this paper is publicly available at https://github.com/josipkh/dimensionless-mpcrl.","short_abstract":"Scaled model experiments are commonly used in various engineering fields to reduce experimentation costs and overcome constraints associated with full-scale systems. The relevance of such experiments relies on dimensional analysis and the principle of dynamic similarity. However, transferring controllers to full-scale...","url_abs":"https://arxiv.org/abs/2512.08667","url_pdf":"https://arxiv.org/pdf/2512.08667v1","authors":"[\"Josip Kir Hromatko\",\"Shambhuraj Sawant\",\"Šandor Ileš\",\"Sébastien Gros\"]","published":"2025-12-09T14:52:15Z","proceeding":"eess.SY","tasks":"[\"eess.SY\",\"cs.LG\"]","methods":"[\"Reinforcement Learning\"]","has_code":false,"code_links":[{"ID":606108,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_id":2831229,"paper_url":"https://arxiv.org/abs/2512.08667","paper_title":"Direct transfer of optimized controllers to similar systems using dimensionless MPC","repo_url":"https://github.com/josipkh/dimensionless-mpcrl","is_official":false,"mentioned_in_paper":false,"mentioned_in_github":true,"github_stars":0}]}