Sliding mode control of robot manipulator's based on neural network reaching law

被引：0

作者：

Chen, Zhimei ^{[1
]}

Zhang, Jinggang ^{[1
]}

Wang, Zhenyan ^{[1
]}

Zeng, Ranchao ^{[1
]}

机构：

[1] Taiyuan Univ Sci & Technol, Sch Elect, Taiyuan, Peoples R China

来源：

2007 IEEE INTERNATIONAL CONFERENCE ON CONTROL AND AUTOMATION, VOLS 1-7 | 2007年

关键词：

feedforward neural network; sliding mode control; reaching law; robot manipulators;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new neural network sliding mode control method of robot manipulators is proposed, which is formed by incorporating sliding mode variable structure control (SWSC) and neural network reaching law. The reaching law parameters are regulated adaptively by two feedforward neural networks (FNNs) respectively. This method converts a multi-input system into n single-input systems. Its control arithmetic is simple and easy to implement. It can not only eliminate the chattering of sliding mode control and strengthen the system robustness, but also improve the character of reaching phase. Tracking errors can promptly converge to a neighborhood of zero. The simulation results of two-degree-of-freedom robot manipulators prove the effectiveness of this scheme.

引用

页码：2862 / 2865

页数：4

共 7 条

[1]

Da Fei-Peng, 1999, Acta Electronica Sinica, V27, P117

[2]

Gao W.B., 1990, VARIABLE STRUCTURE C

[3] NEURAL NETWORKS FOR CONTROL-SYSTEMS - A SURVEY [J].

HUNT, KJ ;

SBARBARO, D ;

ZBIKOWSKI, R ;

GAWTHROP, PJ .

AUTOMATICA, 1992, 28 (06) :1083-1112

[4]

Jalili-Kharaajoo M, 2004, LECT NOTES COMPUT SC, V2972, P892

[5]

NIU YG, 2001, CONTROL DECISION, V16, P79

[6] A fuzzy neural network approximator with fast terminal sliding mode and its applications [J].

Yu, SH ;

Yu, XH ;

Man, ZH .

FUZZY SETS AND SYSTEMS, 2004, 148 (03) :469-486

[7]

Zhang Chang-Fan, 2001, Proceedings of the CSEE, V21, P27

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