Direct adaptive control for a class of MIMO nonlinear systems using neural networks

Please use this identifier to cite or link to this item: https://doi.org/10.1109/TAC.2004.837561

Title:	Direct adaptive control for a class of MIMO nonlinear systems using neural networks
Authors:	Ge, S.S. Li, G.Y. Zhang, J. Lee, T.H.
Keywords:	Adaptive control Discrete-time systems Multiple-input-multiple-output (MIMO) systems Neural networks (NNs)
Issue Date:	Nov-2004
Citation:	Ge, S.S., Li, G.Y., Zhang, J., Lee, T.H. (2004-11). Direct adaptive control for a class of MIMO nonlinear systems using neural networks. IEEE Transactions on Automatic Control 49 (11) : 2001-2006. ScholarBank@NUS Repository. https://doi.org/10.1109/TAC.2004.837561
Abstract:	In this note, direct adaptive neural network (NN) control is studied for a class of multiple-input-multiple-output nonlinear systems based on input-output discrete-time model with unknown interconnections between subsystems. By finding an orthogonai matrix to tune the NN weights, the closed-loop system is proven to be semiglobally uniformly ultimately bounded. The control performance of the closed-loop system is guaranteed by suitably choosing the design parameter. © 2004 IEEE.
Source Title:	IEEE Transactions on Automatic Control
URI:	http://scholarbank.nus.edu.sg/handle/10635/55643
ISSN:	00189286
DOI:	10.1109/TAC.2004.837561
Appears in Collections:	Staff Publications

There are no files associated with this item.

Check