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Proceedings Paper

Sliding mode control based on RBF neural networks
Author(s): Ya Zhou; Wu Wang; Xiao-bo Jiao
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Paper Abstract

Sliding mode control (SMC) is a special nonlinear control method which have quick response, insensitive to parameters variation and disturbance, online identification for plants are not needed, its very suitable for nonlinear system control, but in reality usage, the chattering reduction and elimination is key problem in SMC. A sliding mode controller based on RBF neural network was designed based on RBF networks’ advantages and learning algorithm, the sliding mode controller was realized with adaptive law and the stability of the proposed control scheme is proved by Lyapnouv theorem. Simulation studies show the methods are effective and can applied into linear or nonlinear control system.

Paper Details

Date Published: 13 March 2013
PDF: 6 pages
Proc. SPIE 8783, Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing, 87830I (13 March 2013); doi: 10.1117/12.2013672
Show Author Affiliations
Ya Zhou, Xuchang Univ. (China)
Wu Wang, Xuchang Univ. (China)
Xiao-bo Jiao , Xuchang Electric Power Co. (China)


Published in SPIE Proceedings Vol. 8783:
Fifth International Conference on Machine Vision (ICMV 2012): Computer Vision, Image Analysis and Processing
Yulin Wang; Liansheng Tan; Jianhong Zhou, Editor(s)

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