MIXED OBJECTIVE CONSTRAINED STABLE GENERALIZED PREDICTIVE CONTROL
Constrained stable generalised predictive control (CSGPC) provides a means for handling constraints within the predictive control context and has guaranteed stability properties. However, to guarantee stability, an assumption concerning the feasibility of making the output reach its set-point over a...
| Main Authors: | , , |
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| 格式: | Journal article |
| 語言: | English |
| 出版: |
IEE
1995
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| _version_ | 1826297277203873792 |
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| author | Rossiter, J Kouvaritakis, B Gossner, J |
| author_facet | Rossiter, J Kouvaritakis, B Gossner, J |
| author_sort | Rossiter, J |
| collection | OXFORD |
| description | Constrained stable generalised predictive control (CSGPC) provides a means for handling constraints within the predictive control context and has guaranteed stability properties. However, to guarantee stability, an assumption concerning the feasibility of making the output reach its set-point over a finite horizon is required. If the performance objective is changed from a two-norm of the predicted errors to an infinity-norm, then the finite horizon feasibility assumption is not needed to guarantee stability. As might be expected, though, performance under an infinity-norm objective is often not as good. Here we propose an algorithm which overcomes these difficulties by mixing the two- and infinity-norm objectives. |
| first_indexed | 2024-03-07T04:29:07Z |
| format | Journal article |
| id | oxford-uuid:cdb44e96-58ca-4b67-876a-f462d191cd6c |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-07T04:29:07Z |
| publishDate | 1995 |
| publisher | IEE |
| record_format | dspace |
| spelling | oxford-uuid:cdb44e96-58ca-4b67-876a-f462d191cd6c2022-03-27T07:30:29ZMIXED OBJECTIVE CONSTRAINED STABLE GENERALIZED PREDICTIVE CONTROLJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:cdb44e96-58ca-4b67-876a-f462d191cd6cEnglishSymplectic Elements at OxfordIEE1995Rossiter, JKouvaritakis, BGossner, JConstrained stable generalised predictive control (CSGPC) provides a means for handling constraints within the predictive control context and has guaranteed stability properties. However, to guarantee stability, an assumption concerning the feasibility of making the output reach its set-point over a finite horizon is required. If the performance objective is changed from a two-norm of the predicted errors to an infinity-norm, then the finite horizon feasibility assumption is not needed to guarantee stability. As might be expected, though, performance under an infinity-norm objective is often not as good. Here we propose an algorithm which overcomes these difficulties by mixing the two- and infinity-norm objectives. |
| spellingShingle | Rossiter, J Kouvaritakis, B Gossner, J MIXED OBJECTIVE CONSTRAINED STABLE GENERALIZED PREDICTIVE CONTROL |
| title | MIXED OBJECTIVE CONSTRAINED STABLE GENERALIZED PREDICTIVE CONTROL |
| title_full | MIXED OBJECTIVE CONSTRAINED STABLE GENERALIZED PREDICTIVE CONTROL |
| title_fullStr | MIXED OBJECTIVE CONSTRAINED STABLE GENERALIZED PREDICTIVE CONTROL |
| title_full_unstemmed | MIXED OBJECTIVE CONSTRAINED STABLE GENERALIZED PREDICTIVE CONTROL |
| title_short | MIXED OBJECTIVE CONSTRAINED STABLE GENERALIZED PREDICTIVE CONTROL |
| title_sort | mixed objective constrained stable generalized predictive control |
| work_keys_str_mv | AT rossiterj mixedobjectiveconstrainedstablegeneralizedpredictivecontrol AT kouvaritakisb mixedobjectiveconstrainedstablegeneralizedpredictivecontrol AT gossnerj mixedobjectiveconstrainedstablegeneralizedpredictivecontrol |