Distributed tracking control of uncertain multiple manipulators under switching topologies using neural networks

This data was imported from Scopus:

Authors: Cheng, L., Cheng, M., Yu, H., Deng, L. and Hou, Z.G.

Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volume: 9719

Pages: 233-241

eISSN: 1611-3349

ISBN: 9783319406626

ISSN: 0302-9743

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

© Springer International Publishing Switzerland 2016. 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.

The data on this page was last updated at 04:56 on March 21, 2019.