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However, the objective functions are typically chosen to be close to the real control objectives, despite an objective function that leads to less conservative constraints often provides better closed-loop performance. In this paper, we propose an automatic tuning framework for RMPC in iterative tasks. In particular, we parameterize RMPC and develop a Bayesian optimization (BO) method to tune it by solving a black-box optimization problem. We then introduce an efficient transfer learning framework within BO, which speeds up the searching process and enhances the controller performance. The effectiveness of the proposed tuning framework is illustrated on numerical examples.<\/jats:p>","DOI":"10.1177\/01423312231188871","type":"journal-article","created":{"date-parts":[[2023,9,19]],"date-time":"2023-09-19T06:15:24Z","timestamp":1695104124000},"page":"1362-1373","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Automatic tuning of robust model predictive control in iterative tasks using efficient Bayesian optimization"],"prefix":"10.1177","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7433-0788","authenticated-orcid":false,"given":"Junbo","family":"Tong","sequence":"first","affiliation":[{"name":"Department of Automation, Tsinghua University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuhan","family":"Du","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wenhui","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yueting","family":"Chai","sequence":"additional","affiliation":[{"name":"Department of Automation, Tsinghua University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"179","published-online":{"date-parts":[[2023,9,19]]},"reference":[{"key":"bibr1-01423312231188871","unstructured":"Brochu E, Cora VM, de Freitas N (2010) A tutorial on Bayesian optimization of expensive cost functions, with application to active user modeling and hierarchical reinforcement learning. 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