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Proceedings Paper

Model-free neural control of a class of nonlinear plants
Author(s): Zhong Zheng; Ning Wang
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Paper Abstract

In this paper, a model-free neural controller for a class of nonlinear plants is proposed. Based on the neuron model and its learning strategy for control in reference one, the nonlinear neurocontrol method is designed. After discussing the relationship between the controller gain and the nonlinear system error or error change, the nonlinear function is used to construct the neural network model and the inputs are selected to meet control demands of nonlinear plants. To show the efficiency of the proposed controller, simulation results for the fluid level control in a spherical tank are presented.

Paper Details

Date Published: 2 September 2003
PDF: 4 pages
Proc. SPIE 5253, Fifth International Symposium on Instrumentation and Control Technology, (2 September 2003); doi: 10.1117/12.522169
Show Author Affiliations
Zhong Zheng, Zhejiang Univ. (China)
Ning Wang, Zhejiang Univ. (China)

Published in SPIE Proceedings Vol. 5253:
Fifth International Symposium on Instrumentation and Control Technology
Guangjun Zhang; Huijie Zhao; Zhongyu Wang, Editor(s)

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