Parameter identification for nonlinear time-varying dynamic system based on the assumption of “short time linearly varying” and global constraint optimization
• The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was v...
Ausführliche Beschreibung
Autor*in: |
Chen, Tengfei [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2020 |
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Schlagwörter: |
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Übergeordnetes Werk: |
Enthalten in: Species loss from land use of oil palm plantations in Thailand - Jaroenkietkajorn, Ukrit ELSEVIER, 2021, mssp, Amsterdam [u.a.] |
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Übergeordnetes Werk: |
volume:139 ; year:2020 ; pages:0 |
Links: |
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DOI / URN: |
10.1016/j.ymssp.2020.106620 |
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Katalog-ID: |
ELV049496379 |
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520 | |a • The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was verified through an SDOF numerical example. • A qualitative analysis on the identification window size was carried out. | ||
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10.1016/j.ymssp.2020.106620 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000923.pica (DE-627)ELV049496379 (ELSEVIER)S0888-3270(20)30006-6 DE-627 ger DE-627 rakwb eng 570 630 VZ BIODIV DE-30 fid Chen, Tengfei verfasserin aut Parameter identification for nonlinear time-varying dynamic system based on the assumption of “short time linearly varying” and global constraint optimization 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was verified through an SDOF numerical example. • A qualitative analysis on the identification window size was carried out. Short time linear varying Elsevier Short time invariant Elsevier Nonlinear time-varying dynamic system Elsevier Parameter identification Elsevier Global constraint Elsevier He, Huan oth Chen, Guoping oth Zheng, Yuxuan oth Hou, Shuo oth Xi, Xulong oth Enthalten in Elsevier Jaroenkietkajorn, Ukrit ELSEVIER Species loss from land use of oil palm plantations in Thailand 2021 mssp Amsterdam [u.a.] (DE-627)ELV007151810 volume:139 year:2020 pages:0 https://doi.org/10.1016/j.ymssp.2020.106620 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA AR 139 2020 0 |
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10.1016/j.ymssp.2020.106620 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000923.pica (DE-627)ELV049496379 (ELSEVIER)S0888-3270(20)30006-6 DE-627 ger DE-627 rakwb eng 570 630 VZ BIODIV DE-30 fid Chen, Tengfei verfasserin aut Parameter identification for nonlinear time-varying dynamic system based on the assumption of “short time linearly varying” and global constraint optimization 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was verified through an SDOF numerical example. • A qualitative analysis on the identification window size was carried out. Short time linear varying Elsevier Short time invariant Elsevier Nonlinear time-varying dynamic system Elsevier Parameter identification Elsevier Global constraint Elsevier He, Huan oth Chen, Guoping oth Zheng, Yuxuan oth Hou, Shuo oth Xi, Xulong oth Enthalten in Elsevier Jaroenkietkajorn, Ukrit ELSEVIER Species loss from land use of oil palm plantations in Thailand 2021 mssp Amsterdam [u.a.] (DE-627)ELV007151810 volume:139 year:2020 pages:0 https://doi.org/10.1016/j.ymssp.2020.106620 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA AR 139 2020 0 |
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10.1016/j.ymssp.2020.106620 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000923.pica (DE-627)ELV049496379 (ELSEVIER)S0888-3270(20)30006-6 DE-627 ger DE-627 rakwb eng 570 630 VZ BIODIV DE-30 fid Chen, Tengfei verfasserin aut Parameter identification for nonlinear time-varying dynamic system based on the assumption of “short time linearly varying” and global constraint optimization 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was verified through an SDOF numerical example. • A qualitative analysis on the identification window size was carried out. Short time linear varying Elsevier Short time invariant Elsevier Nonlinear time-varying dynamic system Elsevier Parameter identification Elsevier Global constraint Elsevier He, Huan oth Chen, Guoping oth Zheng, Yuxuan oth Hou, Shuo oth Xi, Xulong oth Enthalten in Elsevier Jaroenkietkajorn, Ukrit ELSEVIER Species loss from land use of oil palm plantations in Thailand 2021 mssp Amsterdam [u.a.] (DE-627)ELV007151810 volume:139 year:2020 pages:0 https://doi.org/10.1016/j.ymssp.2020.106620 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA AR 139 2020 0 |
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10.1016/j.ymssp.2020.106620 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000000923.pica (DE-627)ELV049496379 (ELSEVIER)S0888-3270(20)30006-6 DE-627 ger DE-627 rakwb eng 570 630 VZ BIODIV DE-30 fid Chen, Tengfei verfasserin aut Parameter identification for nonlinear time-varying dynamic system based on the assumption of “short time linearly varying” and global constraint optimization 2020 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was verified through an SDOF numerical example. • A qualitative analysis on the identification window size was carried out. Short time linear varying Elsevier Short time invariant Elsevier Nonlinear time-varying dynamic system Elsevier Parameter identification Elsevier Global constraint Elsevier He, Huan oth Chen, Guoping oth Zheng, Yuxuan oth Hou, Shuo oth Xi, Xulong oth Enthalten in Elsevier Jaroenkietkajorn, Ukrit ELSEVIER Species loss from land use of oil palm plantations in Thailand 2021 mssp Amsterdam [u.a.] (DE-627)ELV007151810 volume:139 year:2020 pages:0 https://doi.org/10.1016/j.ymssp.2020.106620 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA AR 139 2020 0 |
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Parameter identification for nonlinear time-varying dynamic system based on the assumption of “short time linearly varying” and global constraint optimization |
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• The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was verified through an SDOF numerical example. • A qualitative analysis on the identification window size was carried out. |
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• The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was verified through an SDOF numerical example. • A qualitative analysis on the identification window size was carried out. |
abstract_unstemmed |
• The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was verified through an SDOF numerical example. • A qualitative analysis on the identification window size was carried out. |
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code="c">2020</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zzz</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">z</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">nicht spezifiziert</subfield><subfield code="b">zu</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">• The error of the traditional assumption of “short time invariant” was analyzed. • The assumption of “short time linearly varying” with better accuracy was proposed. • A global constraint optimization was introduced to improve the method's robustness. • The proposed identification method was verified through an SDOF numerical example. • A qualitative analysis on the identification window size was carried out.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Short time linear varying</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Short time invariant</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Nonlinear time-varying dynamic system</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Parameter identification</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Global constraint</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">He, Huan</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chen, Guoping</subfield><subfield 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