Adaptive neural backstepping control of nonlinear fractional-order systems with input quantization
被引:1
作者:
Cheng, Chao
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机构:
Beijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing, Peoples R ChinaBeijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing, Peoples R China
Cheng, Chao
[1
]
Wang, Huanqing
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机构:
Bohai Univ, Sch Math, Jinzhou, Peoples R ChinaBeijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing, Peoples R China
Wang, Huanqing
[2
]
Shen, Haikuo
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机构:
Beijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing, Peoples R China
Beijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing 100044, Peoples R ChinaBeijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing, Peoples R China
Shen, Haikuo
[1
,4
]
Liu, Peter X.
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机构:
Carleton Univ, Dept Syst & Comp Engn, Ottawa, ON, CanadaBeijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing, Peoples R China
Liu, Peter X.
[3
]
机构:
[1] Beijing Jiaotong Univ, Sch Mech Elect & Control Engn, Beijing, Peoples R China
[2] Bohai Univ, Sch Math, Jinzhou, Peoples R China
This article addresses the tracking control problem of uncertain fractional-order nonlinear systems in the presence of input quantization and external disturbance. An adaptive backstepping scheme is proposed by combining with radial basis function (RBF) neural networks (NNs), fractional-order disturbance observer (FODO), and backstepping method. The RBF NNs are used to approximate the unknown nonlinearities of fractional-order systems. The FODO is designed to compensate for disturbance and uncertain parameters. The hysteresis quantizer is used to avoid chattering that possibly appears in actual application. The stability of the proposed controller is proved by fractional-order Lyapunov method. In addition, all the signals in the closed-loop system are bounded. The effectiveness of the proposed method is confirmed by the simulation results.
机构:
Hebei Normal Univ, Coll Math & Sci Informat, Shijiazhuang 050024, Hebei, Peoples R China
Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Hebei, Peoples R ChinaHebei Normal Univ, Coll Math & Sci Informat, Shijiazhuang 050024, Hebei, Peoples R China
Ji, Yude
;
Su, Lianqing
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机构:
Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Hebei, Peoples R ChinaHebei Normal Univ, Coll Math & Sci Informat, Shijiazhuang 050024, Hebei, Peoples R China
Su, Lianqing
;
Qiu, Jiqing
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h-index: 0
机构:
Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Hebei, Peoples R ChinaHebei Normal Univ, Coll Math & Sci Informat, Shijiazhuang 050024, Hebei, Peoples R China
机构:
Hebei Normal Univ, Coll Math & Sci Informat, Shijiazhuang 050024, Hebei, Peoples R China
Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Hebei, Peoples R ChinaHebei Normal Univ, Coll Math & Sci Informat, Shijiazhuang 050024, Hebei, Peoples R China
Ji, Yude
;
Su, Lianqing
论文数: 0引用数: 0
h-index: 0
机构:
Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Hebei, Peoples R ChinaHebei Normal Univ, Coll Math & Sci Informat, Shijiazhuang 050024, Hebei, Peoples R China
Su, Lianqing
;
Qiu, Jiqing
论文数: 0引用数: 0
h-index: 0
机构:
Hebei Univ Sci & Technol, Coll Sci, Shijiazhuang 050018, Hebei, Peoples R ChinaHebei Normal Univ, Coll Math & Sci Informat, Shijiazhuang 050024, Hebei, Peoples R China