Neural networked based synchronized control for multiple robotic manipulators

Author

Dongya Zhao ; Quanmin Zhu ; Ning Li ; Shaoyuan Li

Author_Institution

State Key Lab. of Heavy Oil Res., China Univ. of Pet., Qingdao, China

fYear

2013

fDate

12-14 June 2013

Firstpage

1950

Lastpage

1955

Abstract

A novel neural networked based synchronized control approach is developed for multiple robotic manipulators systems (MRMS). An adaptive neural network scheme is used to compensate manipulators modeling uncertainty. The corresponding stability analysis is presented in light of Lyapunov method. Finally, an illustrative example is conducted to validate the proposed approach.

Keywords

Lyapunov methods; adaptive control; manipulators; multi-robot systems; neurocontrollers; stability; synchronisation; Lyapunov method; MRMS; adaptive neural network scheme; manipulator modeling uncertainty; multiple robotic manipulators systems; neural network based synchronized control approach; robotic manipulators; stability analysis; Artificial neural networks; Lead; Manipulator dynamics; Synchronization; Uncertainty;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Automation (ICCA), 2013 10th IEEE International Conference on

Conference_Location

Hangzhou

ISSN

1948-3449

Print_ISBN

978-1-4673-4707-5

Type

conf

DOI

10.1109/ICCA.2013.6564964

Filename

6564964

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=622537