Nonlinear model predictive control with polytopic invariant sets
Ellipsoidal invariant sets have been widely used as target sets in model predictive control (MPC). These sets can be computed by constructing appropriate linear difference inclusions together with additional constraints to ensure that the ellipsoid lies within a given inclusion polytope. The choice...
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| Fformat: | Journal article |
| Iaith: | English |
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2003
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| _version_ | 1826271801610600448 |
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| author | Cannon, M Deshmukh, V Kouvaritakis, B |
| author_facet | Cannon, M Deshmukh, V Kouvaritakis, B |
| author_sort | Cannon, M |
| collection | OXFORD |
| description | Ellipsoidal invariant sets have been widely used as target sets in model predictive control (MPC). These sets can be computed by constructing appropriate linear difference inclusions together with additional constraints to ensure that the ellipsoid lies within a given inclusion polytope. The choice of inclusion polytope has a significant effect on the size of the target ellipsoid, but the optimal inclusion polytope cannot in general be computed systematically. This paper shows that use of polytopic invariant sets overcomes this difficulty, allowing larger stabilizable sets without loss of performance. In the interests of online efficiency, consideration is focused on interpolation-based MPC. © 2003 Elsevier Ltd. All rights reserved. |
| first_indexed | 2024-03-06T22:02:27Z |
| format | Journal article |
| id | oxford-uuid:4f0dd1df-d127-43c9-b9c1-4d11a3ef8b74 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T22:02:27Z |
| publishDate | 2003 |
| record_format | dspace |
| spelling | oxford-uuid:4f0dd1df-d127-43c9-b9c1-4d11a3ef8b742022-03-26T16:04:49ZNonlinear model predictive control with polytopic invariant setsJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:4f0dd1df-d127-43c9-b9c1-4d11a3ef8b74EnglishSymplectic Elements at Oxford2003Cannon, MDeshmukh, VKouvaritakis, BEllipsoidal invariant sets have been widely used as target sets in model predictive control (MPC). These sets can be computed by constructing appropriate linear difference inclusions together with additional constraints to ensure that the ellipsoid lies within a given inclusion polytope. The choice of inclusion polytope has a significant effect on the size of the target ellipsoid, but the optimal inclusion polytope cannot in general be computed systematically. This paper shows that use of polytopic invariant sets overcomes this difficulty, allowing larger stabilizable sets without loss of performance. In the interests of online efficiency, consideration is focused on interpolation-based MPC. © 2003 Elsevier Ltd. All rights reserved. |
| spellingShingle | Cannon, M Deshmukh, V Kouvaritakis, B Nonlinear model predictive control with polytopic invariant sets |
| title | Nonlinear model predictive control with polytopic invariant sets |
| title_full | Nonlinear model predictive control with polytopic invariant sets |
| title_fullStr | Nonlinear model predictive control with polytopic invariant sets |
| title_full_unstemmed | Nonlinear model predictive control with polytopic invariant sets |
| title_short | Nonlinear model predictive control with polytopic invariant sets |
| title_sort | nonlinear model predictive control with polytopic invariant sets |
| work_keys_str_mv | AT cannonm nonlinearmodelpredictivecontrolwithpolytopicinvariantsets AT deshmukhv nonlinearmodelpredictivecontrolwithpolytopicinvariantsets AT kouvaritakisb nonlinearmodelpredictivecontrolwithpolytopicinvariantsets |