Please use this identifier to cite or link to this item: https://doi.org/10.1016/j.neucom.2007.02.012
Title: Adaptive neural network algorithm for control design of rigid-link electrically driven robots
Authors: Huang, S.N. 
Tan, K.K. 
Lee, T.H. 
Keywords: Adaptive control
Neural network
Radial basis function
Robotic systems
Issue Date: Jan-2008
Source: Huang, S.N., Tan, K.K., Lee, T.H. (2008-01). Adaptive neural network algorithm for control design of rigid-link electrically driven robots. Neurocomputing 71 (4-6) : 885-894. ScholarBank@NUS Repository. https://doi.org/10.1016/j.neucom.2007.02.012
Abstract: In this article, an adaptive neural network algorithm is developed for control issue of rigid-link electrically-driven (RLED) robot systems. First, an virtual control algorithm is designed to deal with the mechanical dynamics. Next, an actual neural network controller is used to handle the uncertainty in the mechanical and electrical dynamics. The stability is guaranteed by using a rigid stability proof. Finally, a simulation is given to show the effectiveness of the proposed algorithm. © 2007 Elsevier B.V. All rights reserved.
Source Title: Neurocomputing
URI: http://scholarbank.nus.edu.sg/handle/10635/54914
ISSN: 09252312
DOI: 10.1016/j.neucom.2007.02.012
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