Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.automatica.2008.06.005
Title: Decentralized adaptive controller design of large-scale uncertain robotic systems
Authors: Tan, K.K. 
Huang, S. 
Lee, T.H. 
Keywords: Adaptive control
Large-scale systems
Robotic systems
Issue Date: Jan-2009
Source: Tan, K.K., Huang, S., Lee, T.H. (2009-01). Decentralized adaptive controller design of large-scale uncertain robotic systems. Automatica 45 (1) : 161-166. ScholarBank@NUS Repository. https://doi.org/10.1016/j.automatica.2008.06.005
Abstract: In this paper, we develop a decentralized neural network control design for robotic systems. Using this design, it is not necessary to derive the robotic dynamical system (robotic model) for the control of each of the robotic components, as in traditional robot control. The advantage of the proposed neural network controller is that, under a mild assumption, unknown nonlinear dynamics such as inertia matrix and Coriolis/centripetal matrix and friction, as well as interconnections with arbitrary nonlinear bounds can be accommodated with on-line learning. © 2008 Elsevier Ltd. All rights reserved.
Source Title: Automatica
URI: http://scholarbank.nus.edu.sg/handle/10635/55500
ISSN: 00051098
DOI: 10.1016/j.automatica.2008.06.005
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