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The proposed method uses robust constraints on a detailed model for short-term predictions, while probabilistic constraints are employed on a simplified model with increased sampling time for long-term predictions. The underlying methods are introduced before presenting the proposed Model Predictive Control approach. The advantages of the proposed method are shown in a mobile robot simulation example.<\/jats:p>","DOI":"10.1515\/auto-2021-0025","type":"journal-article","created":{"date-parts":[[2021,9,8]],"date-time":"2021-09-08T21:00:36Z","timestamp":1631134836000},"page":"759-770","source":"Crossref","is-referenced-by-count":1,"title":["Probabilistic model predictive control for extended prediction horizons"],"prefix":"10.1515","volume":"69","author":[{"given":"Tim","family":"Br\u00fcdigam","sequence":"first","affiliation":[{"name":"Chair of Automatic Control Engineering , 9184 Technical University of Munich , Munich , Germany"}]},{"given":"Johannes","family":"Teutsch","sequence":"additional","affiliation":[{"name":"Chair of Automatic Control Engineering , 9184 Technical University of Munich , Munich , Germany"}]},{"given":"Dirk","family":"Wollherr","sequence":"additional","affiliation":[{"name":"Chair of Automatic Control Engineering , 9184 Technical University of Munich , Munich , Germany"}]},{"given":"Marion","family":"Leibold","sequence":"additional","affiliation":[{"name":"Chair of Automatic Control Engineering , 9184 Technical University of Munich , Munich , Germany"}]},{"given":"Martin","family":"Buss","sequence":"additional","affiliation":[{"name":"Chair of Automatic Control Engineering , 9184 Technical University of Munich , Munich , Germany"}]}],"member":"374","published-online":{"date-parts":[[2021,9,9]]},"reference":[{"key":"2023033110360552571_j_auto-2021-0025_ref_001","doi-asserted-by":"crossref","unstructured":"T. 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