Nonlinear gain-based event-triggered tracking control of a marine surface vessel with output constraints
This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with c...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Dong, Sheng [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022transfer abstract |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy - Chang, Guanru ELSEVIER, 2015, Amsterdam [u.a.] |
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| Übergeordnetes Werk: |
volume:262 ; year:2022 ; day:15 ; month:10 ; pages:0 |
| Links: |
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| DOI / URN: |
10.1016/j.oceaneng.2022.112144 |
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| Katalog-ID: |
ELV059090790 |
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| 245 | 1 | 0 | |a Nonlinear gain-based event-triggered tracking control of a marine surface vessel with output constraints |
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| 520 | |a This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. | ||
| 520 | |a This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. | ||
| 650 | 7 | |a Barrier Lyapunov function |2 Elsevier | |
| 650 | 7 | |a Nonlinear gain |2 Elsevier | |
| 650 | 7 | |a Event-triggered |2 Elsevier | |
| 650 | 7 | |a Tracking control |2 Elsevier | |
| 650 | 7 | |a Marine surface vessel |2 Elsevier | |
| 700 | 1 | |a Shen, Zhipeng |4 oth | |
| 700 | 1 | |a Zhou, Lu |4 oth | |
| 700 | 1 | |a Yu, Haomiao |4 oth | |
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10.1016/j.oceaneng.2022.112144 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059090790 (ELSEVIER)S0029-8018(22)01462-7 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Dong, Sheng verfasserin aut Nonlinear gain-based event-triggered tracking control of a marine surface vessel with output constraints 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. Barrier Lyapunov function Elsevier Nonlinear gain Elsevier Event-triggered Elsevier Tracking control Elsevier Marine surface vessel Elsevier Shen, Zhipeng oth Zhou, Lu oth Yu, Haomiao oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112144 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
| spelling |
10.1016/j.oceaneng.2022.112144 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059090790 (ELSEVIER)S0029-8018(22)01462-7 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Dong, Sheng verfasserin aut Nonlinear gain-based event-triggered tracking control of a marine surface vessel with output constraints 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. Barrier Lyapunov function Elsevier Nonlinear gain Elsevier Event-triggered Elsevier Tracking control Elsevier Marine surface vessel Elsevier Shen, Zhipeng oth Zhou, Lu oth Yu, Haomiao oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112144 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
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10.1016/j.oceaneng.2022.112144 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059090790 (ELSEVIER)S0029-8018(22)01462-7 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Dong, Sheng verfasserin aut Nonlinear gain-based event-triggered tracking control of a marine surface vessel with output constraints 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. Barrier Lyapunov function Elsevier Nonlinear gain Elsevier Event-triggered Elsevier Tracking control Elsevier Marine surface vessel Elsevier Shen, Zhipeng oth Zhou, Lu oth Yu, Haomiao oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112144 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
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10.1016/j.oceaneng.2022.112144 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059090790 (ELSEVIER)S0029-8018(22)01462-7 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Dong, Sheng verfasserin aut Nonlinear gain-based event-triggered tracking control of a marine surface vessel with output constraints 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. Barrier Lyapunov function Elsevier Nonlinear gain Elsevier Event-triggered Elsevier Tracking control Elsevier Marine surface vessel Elsevier Shen, Zhipeng oth Zhou, Lu oth Yu, Haomiao oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112144 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
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10.1016/j.oceaneng.2022.112144 doi /cbs_pica/cbs_olc/import_discovery/elsevier/einzuspielen/GBV00000000001918.pica (DE-627)ELV059090790 (ELSEVIER)S0029-8018(22)01462-7 DE-627 ger DE-627 rakwb eng 540 VZ 660 VZ 540 VZ BIODIV DE-30 fid 42.13 bkl Dong, Sheng verfasserin aut Nonlinear gain-based event-triggered tracking control of a marine surface vessel with output constraints 2022transfer abstract nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. Barrier Lyapunov function Elsevier Nonlinear gain Elsevier Event-triggered Elsevier Tracking control Elsevier Marine surface vessel Elsevier Shen, Zhipeng oth Zhou, Lu oth Yu, Haomiao oth Enthalten in Elsevier Science Chang, Guanru ELSEVIER Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy 2015 Amsterdam [u.a.] (DE-627)ELV01276728X volume:262 year:2022 day:15 month:10 pages:0 https://doi.org/10.1016/j.oceaneng.2022.112144 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 42.13 Molekularbiologie VZ AR 262 2022 15 1015 0 |
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Enthalten in Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy Amsterdam [u.a.] volume:262 year:2022 day:15 month:10 pages:0 |
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Enthalten in Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy Amsterdam [u.a.] volume:262 year:2022 day:15 month:10 pages:0 |
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Self-healable hydrogel on tumor cell as drug delivery system for localized and effective therapy |
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Dong, Sheng @@aut@@ Shen, Zhipeng @@oth@@ Zhou, Lu @@oth@@ Yu, Haomiao @@oth@@ |
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Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results.</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. 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nonlinear gain-based event-triggered tracking control of a marine surface vessel with output constraints |
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Nonlinear gain-based event-triggered tracking control of a marine surface vessel with output constraints |
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This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. |
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This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. |
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This paper investigates the tracking control problem of marine surface vessels (MSVs) subject to time-varying output constraints, model uncertainties and unknown external disturbances. Firstly, a nonlinear gain technique is applied to the control design so that the control gain self-regulates with changes in tracking errors. Then, in the case of introducing nonlinear gain, a nonlinear gain-based barrier Lyapunov function (NGBLF) is proposed to guarantee the output tracking errors within predefined time-varying constraints. Subsequently, by employing adaptive neural networks (NNs) to approximate complex uncertainties, a nonlinear gain-based adaptive NN tracking control scheme is developed through the backstepping design tool. Based on this, in order to reduce the update frequency of controllers and mechanical wear of actuators more effectively, while ensuring the control performance, a novel dynamic event-triggered mechanism is incorporated into the control design to tune the thresholds dynamically. Afterwards, the stability analysis indicates that the presented control scheme can guarantee that all signals in the closed-loop system are semi-globally uniformly ultimately bounded and the prescribed time-varying constraints on the tracking errors will not be violated, while the Zeno behavior can be avoided. Finally, the effectiveness of the scheme is verified by simulation results. |
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