[1]ZHANG Wenhui,GAO Jiuzhou,MA Jing,et al.The RBF neural network robust adaptive control of a freefloating space robot[J].CAAI Transactions on Intelligent Systems,2011,6(2):114-118.
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The RBF neural network robust adaptive control of a freefloating space robot

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 6 Number of periods: 2011 2 Page number: 114-118 Column: 学术论文—机器学习 Public date: 2011-04-25
Title:
The RBF neural network robust adaptive control of a freefloating space robot
Author(s):
ZHANG Wenhui1;  GAO Jiuzhou1;  MA Jing2;  QI Naiming1
1.School of Aerospace, Harbin Institute of Technology, Harbin 150001, China;
2. Northeast Agriculture University, Department of Engineering, Harbin 150001, China
Keywords:
neural network;  robust control;  space robot;  adaptive control
CLC:
TP24
DOI:
-
Abstract:
The trajectory tracking of a class of freefloating space robot manipulators with parameter and nonparameter uncertainties was considered. An adaptive robust compensation control algorithm was proposed based on an RBF neural network. Neural networks are used for adaptive learning and compensating the unknown system for parameter uncertainties. The approaching error was eliminated by a sliding controller. The neural network weight adaptive correction laws were obtained based on the Lyapunov analysis approach, which can ensure the convergence of the algorithm. Nonparameter uncertainties were estimated and compensated in real time by a robust controller. The unknown upper bound was shown not to need priori knowledge. This control scheme is easy to use in engineering by introducing a PD feedback and designing a robustness controller in which the neural network is dynamically compensated based on the stability of the whole closed loop system. It was proven that the controller can guarantee the asymptotic convergence of tracking errors, good robustness, and the stability of a closedloop system. The simulation results show that the presented method is effective. 
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