PSO assisted NURB neural network identification
PSO assisted NURB neural network identification
A system identification algorithm is introduced for Hammerstein systems that are modelled using a non-uniform rational B-spline (NURB) neural network. The proposed algorithm consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples including a linear pole assignment controller are utilized to demonstrate the efficacy of the proposed approach.
Hong, Xia
e6551bb3-fbc0-4990-935e-43b706d8c679
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
July 2012
Hong, Xia
e6551bb3-fbc0-4990-935e-43b706d8c679
Chen, Sheng
9310a111-f79a-48b8-98c7-383ca93cbb80
Hong, Xia and Chen, Sheng
(2012)
PSO assisted NURB neural network identification.
8th International Conference on Intelligent Computing, Huangshan Shi, China.
25 - 29 Jul 2012.
11 pp
.
Record type:
Conference or Workshop Item
(Paper)
Abstract
A system identification algorithm is introduced for Hammerstein systems that are modelled using a non-uniform rational B-spline (NURB) neural network. The proposed algorithm consists of two successive stages. First the shaping parameters in NURB network are estimated using a particle swarm optimization (PSO) procedure. Then the remaining parameters are estimated by the method of the singular value decomposition (SVD). Numerical examples including a linear pole assignment controller are utilized to demonstrate the efficacy of the proposed approach.
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e-pub ahead of print date: July 2012
Published date: July 2012
Venue - Dates:
8th International Conference on Intelligent Computing, Huangshan Shi, China, 2012-07-25 - 2012-07-29
Organisations:
Southampton Wireless Group
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Local EPrints ID: 341402
URI: http://eprints.soton.ac.uk/id/eprint/341402
PURE UUID: f0aebc70-1679-430c-b393-9653388bdc6e
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Date deposited: 24 Jul 2012 10:42
Last modified: 14 Mar 2024 11:39
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Contributors
Author:
Xia Hong
Author:
Sheng Chen
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