Online learning constrained model predictive control based on double prediction
A data-based predictive controller is proposed, offering both robust stability guarantees and online learning capabilities. To merge these two properties in a single controller, a double-prediction approach is taken. On the one hand, a safe prediction is computed using Lipschitz interpolation on the...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
| Published: |
Wiley
2020
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| _version_ | 1797090753124499456 |
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| author | Manzano, JM Muñoz de la Peña, D Calliess, J-P Limon, D |
| author_facet | Manzano, JM Muñoz de la Peña, D Calliess, J-P Limon, D |
| author_sort | Manzano, JM |
| collection | OXFORD |
| description | A data-based predictive controller is proposed, offering both robust stability guarantees and online learning capabilities. To merge these two properties in a single controller, a double-prediction approach is taken. On the one hand, a safe prediction is computed using Lipschitz interpolation on the basis of an offline identification dataset, which guarantees safety of the controlled system. On the other hand, the controller also benefits from the use of a second online learning-based prediction as measurements incrementally become available over time. Sufficient conditions for robust stability and constraint satisfaction are given. Illustrations of the approach are provided in a simulated case study. |
| first_indexed | 2024-03-07T03:23:13Z |
| format | Journal article |
| id | oxford-uuid:b826e6cc-3636-4d3d-99f9-8599304b1135 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T03:23:13Z |
| publishDate | 2020 |
| publisher | Wiley |
| record_format | dspace |
| spelling | oxford-uuid:b826e6cc-3636-4d3d-99f9-8599304b11352022-03-27T04:53:58ZOnline learning constrained model predictive control based on double predictionJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:b826e6cc-3636-4d3d-99f9-8599304b1135EnglishSymplectic ElementsWiley2020Manzano, JMMuñoz de la Peña, DCalliess, J-PLimon, DA data-based predictive controller is proposed, offering both robust stability guarantees and online learning capabilities. To merge these two properties in a single controller, a double-prediction approach is taken. On the one hand, a safe prediction is computed using Lipschitz interpolation on the basis of an offline identification dataset, which guarantees safety of the controlled system. On the other hand, the controller also benefits from the use of a second online learning-based prediction as measurements incrementally become available over time. Sufficient conditions for robust stability and constraint satisfaction are given. Illustrations of the approach are provided in a simulated case study. |
| spellingShingle | Manzano, JM Muñoz de la Peña, D Calliess, J-P Limon, D Online learning constrained model predictive control based on double prediction |
| title | Online learning constrained model predictive control based on double prediction |
| title_full | Online learning constrained model predictive control based on double prediction |
| title_fullStr | Online learning constrained model predictive control based on double prediction |
| title_full_unstemmed | Online learning constrained model predictive control based on double prediction |
| title_short | Online learning constrained model predictive control based on double prediction |
| title_sort | online learning constrained model predictive control based on double prediction |
| work_keys_str_mv | AT manzanojm onlinelearningconstrainedmodelpredictivecontrolbasedondoubleprediction AT munozdelapenad onlinelearningconstrainedmodelpredictivecontrolbasedondoubleprediction AT calliessjp onlinelearningconstrainedmodelpredictivecontrolbasedondoubleprediction AT limond onlinelearningconstrainedmodelpredictivecontrolbasedondoubleprediction |