The control method of adaptive backstepping and neural network in the application of a parallel robot

Author

Gao, Guoqin ; Yan, Qin ; Wu, Yanzhong

Author_Institution

Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang, China

Volume

3

fYear

2010

fDate

10-12 Aug. 2010

Firstpage

1397

Lastpage

1400

Abstract

Considering the unknown nonlinearities and external disturbances for a 2-DOF redundant parallel robot, a novel control method based on adaptive backstepping control and neural network approximation is proposed. In the controller, a RBF NN is used to approximate the uncertain function in order to make the adaptive backstepping control have a strong robustness for the unknown nonlinearities and external disturbances. The simulation results show that the control method has a good performance of tracking and a strong robustness, which can improve the control performance of a parallel robot with a strong coupling and high non-linearity. They also confirm the correctness and effectiveness of the proposed control strategy.

Keywords

adaptive control; control nonlinearities; manipulators; radial basis function networks; robust control; 2-DOF redundant parallel robot; RBF NN; adaptive backstepping control method; neural network approximation; nonlinearities; robustness; Adaptive systems; Approximation methods; Artificial neural networks; Backstepping; Control systems; Mathematical model; Parallel robots; Parallel robot; RBF; backstepping; robustness;

fLanguage

English

Publisher

ieee

Conference_Titel

Natural Computation (ICNC), 2010 Sixth International Conference on

Conference_Location

Yantai, Shandong

Print_ISBN

978-1-4244-5958-2

Type

conf

DOI

10.1109/ICNC.2010.5582540

Filename

5582540