Model predictive control for tracking randomly varying references
This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established....
Ausführliche Beschreibung
Autor*in: |
Falugi, Paola [verfasserIn] |
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Format: |
Artikel |
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Sprache: |
Englisch |
Erschienen: |
2015 |
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Rechteinformationen: |
Nutzungsrecht: © 2014 Taylor & Francis 2015 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: International journal of control - London : Taylor & Francis, 1965, 88(2015), 4, Seite 745-753 |
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Übergeordnetes Werk: |
volume:88 ; year:2015 ; number:4 ; pages:745-753 |
Links: |
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DOI / URN: |
10.1080/00207179.2014.972464 |
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Katalog-ID: |
OLC1962645770 |
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10.1080/00207179.2014.972464 doi PQ20160617 (DE-627)OLC1962645770 (DE-599)GBVOLC1962645770 (PRQ)c2126-65e9c43b6e53262b332520bfa833a80b5455d79b0d27857b362cd02099bc53200 (KEY)0006630320150000088000400745modelpredictivecontrolfortrackingrandomlyvaryingre DE-627 ger DE-627 rakwb eng 620 DNB Falugi, Paola verfasserin aut Model predictive control for tracking randomly varying references 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterise the set to which the tracking error converges and the associated region of convergence. Nutzungsrecht: © 2014 Taylor & Francis 2015 tracking control constrained nonlinear systems nonlinear model predictive control Predictive control Enthalten in International journal of control London : Taylor & Francis, 1965 88(2015), 4, Seite 745-753 (DE-627)129595780 (DE-600)240693-7 (DE-576)015088804 0020-7179 nnns volume:88 year:2015 number:4 pages:745-753 http://dx.doi.org/10.1080/00207179.2014.972464 Volltext http://www.tandfonline.com/doi/abs/10.1080/00207179.2014.972464 http://search.proquest.com/docview/1661793991 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_21 GBV_ILN_70 GBV_ILN_2020 GBV_ILN_4314 GBV_ILN_4318 GBV_ILN_4700 AR 88 2015 4 745-753 |
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10.1080/00207179.2014.972464 doi PQ20160617 (DE-627)OLC1962645770 (DE-599)GBVOLC1962645770 (PRQ)c2126-65e9c43b6e53262b332520bfa833a80b5455d79b0d27857b362cd02099bc53200 (KEY)0006630320150000088000400745modelpredictivecontrolfortrackingrandomlyvaryingre DE-627 ger DE-627 rakwb eng 620 DNB Falugi, Paola verfasserin aut Model predictive control for tracking randomly varying references 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterise the set to which the tracking error converges and the associated region of convergence. Nutzungsrecht: © 2014 Taylor & Francis 2015 tracking control constrained nonlinear systems nonlinear model predictive control Predictive control Enthalten in International journal of control London : Taylor & Francis, 1965 88(2015), 4, Seite 745-753 (DE-627)129595780 (DE-600)240693-7 (DE-576)015088804 0020-7179 nnns volume:88 year:2015 number:4 pages:745-753 http://dx.doi.org/10.1080/00207179.2014.972464 Volltext http://www.tandfonline.com/doi/abs/10.1080/00207179.2014.972464 http://search.proquest.com/docview/1661793991 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_21 GBV_ILN_70 GBV_ILN_2020 GBV_ILN_4314 GBV_ILN_4318 GBV_ILN_4700 AR 88 2015 4 745-753 |
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10.1080/00207179.2014.972464 doi PQ20160617 (DE-627)OLC1962645770 (DE-599)GBVOLC1962645770 (PRQ)c2126-65e9c43b6e53262b332520bfa833a80b5455d79b0d27857b362cd02099bc53200 (KEY)0006630320150000088000400745modelpredictivecontrolfortrackingrandomlyvaryingre DE-627 ger DE-627 rakwb eng 620 DNB Falugi, Paola verfasserin aut Model predictive control for tracking randomly varying references 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterise the set to which the tracking error converges and the associated region of convergence. Nutzungsrecht: © 2014 Taylor & Francis 2015 tracking control constrained nonlinear systems nonlinear model predictive control Predictive control Enthalten in International journal of control London : Taylor & Francis, 1965 88(2015), 4, Seite 745-753 (DE-627)129595780 (DE-600)240693-7 (DE-576)015088804 0020-7179 nnns volume:88 year:2015 number:4 pages:745-753 http://dx.doi.org/10.1080/00207179.2014.972464 Volltext http://www.tandfonline.com/doi/abs/10.1080/00207179.2014.972464 http://search.proquest.com/docview/1661793991 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_21 GBV_ILN_70 GBV_ILN_2020 GBV_ILN_4314 GBV_ILN_4318 GBV_ILN_4700 AR 88 2015 4 745-753 |
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10.1080/00207179.2014.972464 doi PQ20160617 (DE-627)OLC1962645770 (DE-599)GBVOLC1962645770 (PRQ)c2126-65e9c43b6e53262b332520bfa833a80b5455d79b0d27857b362cd02099bc53200 (KEY)0006630320150000088000400745modelpredictivecontrolfortrackingrandomlyvaryingre DE-627 ger DE-627 rakwb eng 620 DNB Falugi, Paola verfasserin aut Model predictive control for tracking randomly varying references 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterise the set to which the tracking error converges and the associated region of convergence. Nutzungsrecht: © 2014 Taylor & Francis 2015 tracking control constrained nonlinear systems nonlinear model predictive control Predictive control Enthalten in International journal of control London : Taylor & Francis, 1965 88(2015), 4, Seite 745-753 (DE-627)129595780 (DE-600)240693-7 (DE-576)015088804 0020-7179 nnns volume:88 year:2015 number:4 pages:745-753 http://dx.doi.org/10.1080/00207179.2014.972464 Volltext http://www.tandfonline.com/doi/abs/10.1080/00207179.2014.972464 http://search.proquest.com/docview/1661793991 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC GBV_ILN_21 GBV_ILN_70 GBV_ILN_2020 GBV_ILN_4314 GBV_ILN_4318 GBV_ILN_4700 AR 88 2015 4 745-753 |
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This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterise the set to which the tracking error converges and the associated region of convergence. |
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This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterise the set to which the tracking error converges and the associated region of convergence. |
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This paper proposes a model predictive control scheme for tracking a-priori unknown references varying in a wide range and analyses its performance. It is usual to assume that the reference eventually converges to a constant in which case convergence to zero of the tracking error can be established. In this note we remove this simplifying assumption and characterise the set to which the tracking error converges and the associated region of convergence. |
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Model predictive control for tracking randomly varying references |
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