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New dynamic RBF neural network controller
Ya-Min Wan   Sun-An Wang  
Dept. of Mechatronics Eng., Xi'an Jiaotong Univ., China;

This paper appears in: Machine Learning and Cybernetics, 2004. Proceedings of 2004 International Conference on
Publication Date: 26-29 Aug. 2004
Volume: 6,  On page(s): 3379- 3382 vol.6
ISSN:
ISBN: 0-7803-8403-2
INSPEC Accession Number: 8254298
Current Version Published: 2005-01-24

Abstract
It isn't very effective to use RBF neural network as controller to deal with dynamic systems. So a new dynamic radial basis function network including feedback unit is proposed. The universal approximation theorem of DRBF is proved according to Stone-Weierstrass theorem. The intelligent controller based on this dynamic network is employed to deal with hydraulic position servo system. And learning algorithm based on integrative object function is deduced. The experiment results show that the intelligent controller has adaptability and robustness, and controller's design does not depend on the system's model.

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