Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves
• The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder acti...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wang, Yuanyuan [verfasserIn] |
|---|
| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2017 |
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| Schlagwörter: |
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| Umfang: |
13 |
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| Übergeordnetes Werk: |
Enthalten in: P-602 - The attitudes of students of high schools in Gjilan related to drug abuse - 2012, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:68 ; year:2017 ; pages:26-38 ; extent:13 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.apor.2017.08.007 |
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| 520 | |a • The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost. | ||
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10.1016/j.apor.2017.08.007 doi GBV00000000000374.pica (DE-627)ELV030224853 (ELSEVIER)S0141-1187(16)30572-7 DE-627 ger DE-627 rakwb eng 610 VZ 530 VZ 33.00 bkl Wang, Yuanyuan verfasserin aut Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves 2017 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost. Trajectory tracking Elsevier Neural networks Elsevier Rudder roll stabilization system Elsevier Unscented Kalman Filter training Elsevier Chai, Shuhong oth Khan, Faisal oth Nguyen, Hung Duc oth Enthalten in Elsevier Science P-602 - The attitudes of students of high schools in Gjilan related to drug abuse 2012 Amsterdam [u.a.] (DE-627)ELV011183217 volume:68 year:2017 pages:26-38 extent:13 https://doi.org/10.1016/j.apor.2017.08.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 68 2017 26-38 13 |
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10.1016/j.apor.2017.08.007 doi GBV00000000000374.pica (DE-627)ELV030224853 (ELSEVIER)S0141-1187(16)30572-7 DE-627 ger DE-627 rakwb eng 610 VZ 530 VZ 33.00 bkl Wang, Yuanyuan verfasserin aut Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves 2017 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost. Trajectory tracking Elsevier Neural networks Elsevier Rudder roll stabilization system Elsevier Unscented Kalman Filter training Elsevier Chai, Shuhong oth Khan, Faisal oth Nguyen, Hung Duc oth Enthalten in Elsevier Science P-602 - The attitudes of students of high schools in Gjilan related to drug abuse 2012 Amsterdam [u.a.] (DE-627)ELV011183217 volume:68 year:2017 pages:26-38 extent:13 https://doi.org/10.1016/j.apor.2017.08.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 68 2017 26-38 13 |
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10.1016/j.apor.2017.08.007 doi GBV00000000000374.pica (DE-627)ELV030224853 (ELSEVIER)S0141-1187(16)30572-7 DE-627 ger DE-627 rakwb eng 610 VZ 530 VZ 33.00 bkl Wang, Yuanyuan verfasserin aut Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves 2017 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost. Trajectory tracking Elsevier Neural networks Elsevier Rudder roll stabilization system Elsevier Unscented Kalman Filter training Elsevier Chai, Shuhong oth Khan, Faisal oth Nguyen, Hung Duc oth Enthalten in Elsevier Science P-602 - The attitudes of students of high schools in Gjilan related to drug abuse 2012 Amsterdam [u.a.] (DE-627)ELV011183217 volume:68 year:2017 pages:26-38 extent:13 https://doi.org/10.1016/j.apor.2017.08.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 68 2017 26-38 13 |
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10.1016/j.apor.2017.08.007 doi GBV00000000000374.pica (DE-627)ELV030224853 (ELSEVIER)S0141-1187(16)30572-7 DE-627 ger DE-627 rakwb eng 610 VZ 530 VZ 33.00 bkl Wang, Yuanyuan verfasserin aut Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves 2017 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost. Trajectory tracking Elsevier Neural networks Elsevier Rudder roll stabilization system Elsevier Unscented Kalman Filter training Elsevier Chai, Shuhong oth Khan, Faisal oth Nguyen, Hung Duc oth Enthalten in Elsevier Science P-602 - The attitudes of students of high schools in Gjilan related to drug abuse 2012 Amsterdam [u.a.] (DE-627)ELV011183217 volume:68 year:2017 pages:26-38 extent:13 https://doi.org/10.1016/j.apor.2017.08.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 68 2017 26-38 13 |
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10.1016/j.apor.2017.08.007 doi GBV00000000000374.pica (DE-627)ELV030224853 (ELSEVIER)S0141-1187(16)30572-7 DE-627 ger DE-627 rakwb eng 610 VZ 530 VZ 33.00 bkl Wang, Yuanyuan verfasserin aut Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves 2017 13 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier • The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost. Trajectory tracking Elsevier Neural networks Elsevier Rudder roll stabilization system Elsevier Unscented Kalman Filter training Elsevier Chai, Shuhong oth Khan, Faisal oth Nguyen, Hung Duc oth Enthalten in Elsevier Science P-602 - The attitudes of students of high schools in Gjilan related to drug abuse 2012 Amsterdam [u.a.] (DE-627)ELV011183217 volume:68 year:2017 pages:26-38 extent:13 https://doi.org/10.1016/j.apor.2017.08.007 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U 33.00 Physik: Allgemeines VZ AR 68 2017 26-38 13 |
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Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves |
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• The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost. |
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• The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost. |
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• The desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost. |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">ELV030224853</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230623204134.0</controlfield><controlfield tag="007">cr uuu---uuuuu</controlfield><controlfield tag="008">180603s2017 xx |||||o 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1016/j.apor.2017.08.007</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">GBV00000000000374.pica</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)ELV030224853</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ELSEVIER)S0141-1187(16)30572-7</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">610</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">530</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">33.00</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Wang, Yuanyuan</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Unscented Kalman Filter trained neural networks based rudder roll stabilization system for ship in waves</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2017</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">13</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 desired feedback RBFNN based control algorithm which adopts a modified UKF method for weights updating was formulated. • The rudder roll stabilization system utilizing UKF RBFNN was proposed. • Roll damping and trajectory tracking for ships were simultaneously achieved only through rudder actions. • In comparison with the BP RBFNN control system and PD control system, the proposed system has demonstrated profound advantages of roll damping capability with low cost.</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Trajectory tracking</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Neural networks</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Rudder roll stabilization system</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="650" ind1=" " ind2="7"><subfield code="a">Unscented Kalman Filter training</subfield><subfield code="2">Elsevier</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Chai, Shuhong</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Khan, Faisal</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Nguyen, Hung Duc</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="n">Elsevier Science</subfield><subfield code="t">P-602 - 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