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|Title:||Adaptive neural network algorithm for control design of rigid-link electrically driven robots||Authors:||Huang, S.N.
Radial basis function
|Issue Date:||Jan-2008||Citation:||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|
|Appears in Collections:||Staff Publications|
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