DocumentCode
1867450
Title
Robust tracking control of space robot via neural network
Author
Feng, Baomin ; Ma, Guangcheng ; Xie, Weinan ; Wang, Changhong
Author_Institution
Space Control & Inertia Technol. Res. Center, Harbin Inst. of Technol.
fYear
2006
fDate
19-21 Jan. 2006
Lastpage
906
Abstract
This paper proposes a new robust control method for space robot by using neural network. A radial-basis-function (RBF) neural network is included to compensate for the system uncertainties. The parameters of the neural network are adapted on-line according to derived learning algorithms using Lyapunov method. Simulation results of a two-link planar space robot verify the validity of the proposed controller in the presence of uncertainties
Keywords
Lyapunov methods; aerospace robotics; learning (artificial intelligence); radial basis function networks; robust control; tracking; Lyapunov method; radial-basis-function neural network; robust tracking control; space robots; Control systems; Manipulator dynamics; Mobile robots; Neural networks; Orbital robotics; Robot control; Robust control; Space missions; Space stations; Space technology;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems and Control in Aerospace and Astronautics, 2006. ISSCAA 2006. 1st International Symposium on
Conference_Location
Harbin
Print_ISBN
0-7803-9395-3
Type
conf
DOI
10.1109/ISSCAA.2006.1627472
Filename
1627472
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