Distributed Tracking Control of Uncertain Multiple Manipulators Under Switching Topologies Using Neural Networks

被引：7

作者：

Cheng, Long ^{[1
]}

Cheng, Ming ^{[2
]}

Yu, Hongnian ^{[3
]}

Deng, Lu ^{[4
]}

Hou, Zeng-Guang ^{[1
]}

机构：

[1] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China

[2] Harbin Inst Petr, Dept Petr Engn, Harbin 150028, Peoples R China

[3] Bournemouth Univ, Dept Comp, Poole BH12 5BB, Dorset, England

[4] Cent Univ Finance & Econ, Sch Math & Stat, Beijing 100081, Peoples R China

来源：

ADVANCES IN NEURAL NETWORKS - ISNN 2016 | 2016年 / 9719卷

关键词：

Leader-following problem; Manipulator; Uncertainty; Neural networks; Switching topologies; EULER-LAGRANGE SYSTEMS; ADAPTIVE CONSENSUS; SYNCHRONIZATION; DYNAMICS;

D O I：

10.1007/978-3-319-40663-3_27

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The distributed tracking control of a group of manipulators under switching directed topologies is studied. Each manipulator is modeled by the Euler-Lagrange dynamics which includes uncertainties and external disturbances. The proposed controller has the neural network approximation unit for compensating uncertainties and the robust term for counteracting external disturbances. It can be proved that when the communication topology switches among a set of graphes which have a spanning tree and have no loop structure, the final tracking error can be reduced as small as possible.

引用

页码：233 / 241

页数：9

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