Explicit use of probabilistic distributions in linear predictive control
The guarantee of feasibility given feasibility at initial time is an issue that has been overlooked by many of the recent papers on stochastic model predictive control. Effective solutions have recently been proposed, but these carry considerable online computational load and a degree of conservativ...
| Autores principales: | , , , |
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| Formato: | Journal article |
| Lenguaje: | English |
| Publicado: |
2010
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| _version_ | 1826295687437877248 |
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| author | Kouvaritakis, B Cannon, M Rakovic, S Cheng, Q |
| author_facet | Kouvaritakis, B Cannon, M Rakovic, S Cheng, Q |
| author_sort | Kouvaritakis, B |
| collection | OXFORD |
| description | The guarantee of feasibility given feasibility at initial time is an issue that has been overlooked by many of the recent papers on stochastic model predictive control. Effective solutions have recently been proposed, but these carry considerable online computational load and a degree of conservativism. For the case that the elements of the random additive disturbance vector are independent, the current paper ensures that probabilistic constraints are met and that a quadratic stability condition is satisfied. A numerical example illustrates the efficacy of the proposed algorithm, which achieves tight satisfaction of constraints and thereby attains near-optimal performance. |
| first_indexed | 2024-03-07T04:04:53Z |
| format | Journal article |
| id | oxford-uuid:c5cd75f4-040c-4476-ac1c-61de7e5858bb |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:04:53Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | oxford-uuid:c5cd75f4-040c-4476-ac1c-61de7e5858bb2022-03-27T06:33:47ZExplicit use of probabilistic distributions in linear predictive controlJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:c5cd75f4-040c-4476-ac1c-61de7e5858bbEnglishSymplectic Elements at Oxford2010Kouvaritakis, BCannon, MRakovic, SCheng, QThe guarantee of feasibility given feasibility at initial time is an issue that has been overlooked by many of the recent papers on stochastic model predictive control. Effective solutions have recently been proposed, but these carry considerable online computational load and a degree of conservativism. For the case that the elements of the random additive disturbance vector are independent, the current paper ensures that probabilistic constraints are met and that a quadratic stability condition is satisfied. A numerical example illustrates the efficacy of the proposed algorithm, which achieves tight satisfaction of constraints and thereby attains near-optimal performance. |
| spellingShingle | Kouvaritakis, B Cannon, M Rakovic, S Cheng, Q Explicit use of probabilistic distributions in linear predictive control |
| title | Explicit use of probabilistic distributions in linear predictive control |
| title_full | Explicit use of probabilistic distributions in linear predictive control |
| title_fullStr | Explicit use of probabilistic distributions in linear predictive control |
| title_full_unstemmed | Explicit use of probabilistic distributions in linear predictive control |
| title_short | Explicit use of probabilistic distributions in linear predictive control |
| title_sort | explicit use of probabilistic distributions in linear predictive control |
| work_keys_str_mv | AT kouvaritakisb explicituseofprobabilisticdistributionsinlinearpredictivecontrol AT cannonm explicituseofprobabilisticdistributionsinlinearpredictivecontrol AT rakovics explicituseofprobabilisticdistributionsinlinearpredictivecontrol AT chengq explicituseofprobabilisticdistributionsinlinearpredictivecontrol |