Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay
In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter a...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Niu, Ben [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2016transfer abstract |
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| Schlagwörter: |
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| Umfang: |
8 |
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| Übergeordnetes Werk: |
Enthalten in: The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast - Liu, Yang ELSEVIER, 2018, an international journal, Amsterdam |
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| Übergeordnetes Werk: |
volume:173 ; year:2016 ; day:15 ; month:01 ; pages:2121-2128 ; extent:8 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.neucom.2015.10.059 |
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ELV014238950 |
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| 520 | |a In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. | ||
| 520 | |a In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. | ||
| 650 | 7 | |a Input delay |2 Elsevier | |
| 650 | 7 | |a Switched nonlinear system |2 Elsevier | |
| 650 | 7 | |a Neural network |2 Elsevier | |
| 650 | 7 | |a Adaptive control |2 Elsevier | |
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10.1016/j.neucom.2015.10.059 doi GBVA2016014000027.pica (DE-627)ELV014238950 (ELSEVIER)S0925-2312(15)01518-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Niu, Ben verfasserin aut Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. Input delay Elsevier Switched nonlinear system Elsevier Neural network Elsevier Adaptive control Elsevier Li, Lu oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:173 year:2016 day:15 month:01 pages:2121-2128 extent:8 https://doi.org/10.1016/j.neucom.2015.10.059 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 173 2016 15 0115 2121-2128 8 045F 610 |
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10.1016/j.neucom.2015.10.059 doi GBVA2016014000027.pica (DE-627)ELV014238950 (ELSEVIER)S0925-2312(15)01518-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Niu, Ben verfasserin aut Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. Input delay Elsevier Switched nonlinear system Elsevier Neural network Elsevier Adaptive control Elsevier Li, Lu oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:173 year:2016 day:15 month:01 pages:2121-2128 extent:8 https://doi.org/10.1016/j.neucom.2015.10.059 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 173 2016 15 0115 2121-2128 8 045F 610 |
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10.1016/j.neucom.2015.10.059 doi GBVA2016014000027.pica (DE-627)ELV014238950 (ELSEVIER)S0925-2312(15)01518-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Niu, Ben verfasserin aut Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. Input delay Elsevier Switched nonlinear system Elsevier Neural network Elsevier Adaptive control Elsevier Li, Lu oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:173 year:2016 day:15 month:01 pages:2121-2128 extent:8 https://doi.org/10.1016/j.neucom.2015.10.059 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 173 2016 15 0115 2121-2128 8 045F 610 |
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10.1016/j.neucom.2015.10.059 doi GBVA2016014000027.pica (DE-627)ELV014238950 (ELSEVIER)S0925-2312(15)01518-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Niu, Ben verfasserin aut Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. Input delay Elsevier Switched nonlinear system Elsevier Neural network Elsevier Adaptive control Elsevier Li, Lu oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:173 year:2016 day:15 month:01 pages:2121-2128 extent:8 https://doi.org/10.1016/j.neucom.2015.10.059 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 173 2016 15 0115 2121-2128 8 045F 610 |
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10.1016/j.neucom.2015.10.059 doi GBVA2016014000027.pica (DE-627)ELV014238950 (ELSEVIER)S0925-2312(15)01518-0 DE-627 ger DE-627 rakwb eng 610 610 DE-600 570 VZ BIODIV DE-30 fid 35.70 bkl 42.12 bkl Niu, Ben verfasserin aut Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay 2016transfer abstract 8 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. Input delay Elsevier Switched nonlinear system Elsevier Neural network Elsevier Adaptive control Elsevier Li, Lu oth Enthalten in Elsevier Liu, Yang ELSEVIER The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast 2018 an international journal Amsterdam (DE-627)ELV002603926 volume:173 year:2016 day:15 month:01 pages:2121-2128 extent:8 https://doi.org/10.1016/j.neucom.2015.10.059 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U FID-BIODIV SSG-OLC-PHA 35.70 Biochemie: Allgemeines VZ 42.12 Biophysik VZ AR 173 2016 15 0115 2121-2128 8 045F 610 |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay |
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Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay |
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Niu, Ben |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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The TORC1 signaling pathway regulates respiration-induced mitophagy in yeast |
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10.1016/j.neucom.2015.10.059 |
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adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay |
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Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay |
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In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. |
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In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. |
| abstract_unstemmed |
In this paper, a neural-network-based control scheme is developed for the tracking control problem of a class of switched strict-feedback nonlinear systems with uncertain input delay and external time-varying disturbances. First, the auxiliary signals are obtained by masterly constructing a filter and a virtual observer. Then the adaptive backstepping technique and neural network (NN) are employed to construct a common Lyapunov function (CLF) and a state feedback controller for all subsystems. It is proved that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and that the tracking error ultimately converges to an adequately small compact set. Finally, a simulation example is given to illustrate the effectiveness of the proposed control approach. |
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Adaptive neural network tracking control for a class of switched strict-feedback nonlinear systems with input delay |
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https://doi.org/10.1016/j.neucom.2015.10.059 |
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