Please use this identifier to cite or link to this item:
|Title:||Adaptive control of mechanical systems using neural networks||Authors:||Huang, S.
Neural networks (NNs)
|Issue Date:||Sep-2007||Citation:||Huang, S., Tan, K.K., Lee, T.H., Putra, A.S. (2007-09). Adaptive control of mechanical systems using neural networks. IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews 37 (5) : 897-903. ScholarBank@NUS Repository. https://doi.org/10.1109/TSMCC.2007.900660||Abstract:||In this paper, we consider the decentralized adaptive control design problem for uncertain mechanical systems, where uncertainty may arise due to isolated subsystem and/or interconnections among subsystems. Radial basis function neural networks are used to approximate the nonlinear functions to include both dynamic and interconnection uncertainties in each subsystem. The stability of the thus designed control system can be guaranteed by a rigid proof. Finally, a simulation example is given to illustrate the effectiveness of the proposed algorithm. © 2007 IEEE.||Source Title:||IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews||URI:||http://scholarbank.nus.edu.sg/handle/10635/54891||ISSN:||10946977||DOI:||10.1109/TSMCC.2007.900660|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Oct 22, 2019
WEB OF SCIENCETM
checked on Oct 15, 2019
checked on Oct 13, 2019
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.