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Synchronized control with neuro-agents for leader-follower based multiple robotic manipulators

Zhao, Dongya; Zhu, Quanmin; Li, Ning; Li, Shaoyuan

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Authors

Dongya Zhao

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Quan Zhu Quan.Zhu@uwe.ac.uk
Professor in Control Systems

Ning Li

Shaoyuan Li



Abstract

In this paper, a new neural network enhanced synchronized control approach is proposed for multiple robotic manipulators systems (MRMS) based on the leader-follower network communication topology. The justification of introducing two adaptive Radial Basis Function Neural Networks (RBF NN), also called neuro-agents, is to facilitate the whole control system design and analysis. Otherwise such design is impossible with classical analytical procedure. The first agent is the neuro-compensator to accommodate uncertainty associated with the follower manipulators, and the second agent is the neuro-estimator to obtain acceleration of the leader manipulator. Correspondingly the stability analysis of the designed control system is formulated with Lyapunov method. Finally numerical bench tests under various critical conditions are conducted to validate the effectiveness of the proposed approach. © 2013 Elsevier B.V.

Citation

Zhao, D., Zhu, Q., Li, N., & Li, S. (2014). Synchronized control with neuro-agents for leader-follower based multiple robotic manipulators. Neurocomputing, 124, 149-161. https://doi.org/10.1016/j.neucom.2013.07.016

Journal Article Type Article
Acceptance Date Jul 19, 2013
Online Publication Date Sep 7, 2013
Publication Date Jan 26, 2014
Deposit Date Jan 20, 2015
Publicly Available Date Feb 9, 2016
Journal Neurocomputing
Print ISSN 0925-2312
Electronic ISSN 1872-8286
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 124
Pages 149-161
DOI https://doi.org/10.1016/j.neucom.2013.07.016
Keywords Synchronized control;
multiple robotic manipulators, leader–follower, neural networks, neuro-computing
Public URL https://uwe-repository.worktribe.com/output/822639
Publisher URL http://dx.doi.org/10.1016/j.neucom.2013.07.016

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