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Application of information fusion based on RBF neural networks and fuzzy control to ball mill pulverizing system

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4 Author(s)
Gangquan Si ; Sch. of Electr. Eng., Xi''an Jiao Tong Univ., Xi''an ; Hui Cao ; Yanbin Zhang ; Lixin Jia

Ball mill pulverizing system is a typical multi-input and multi-output (MIMO) system with the characteristics as strong coupling, nonlinearity, large delay and time-varying. The running conditions and the precise mathematic model of the system can not be obtained easily for its complex characteristics, so the conventional control strategy is not effective. An information fusion based method including multi-sensors, data preprocessing, RBF neural networks, fuzzy controller is put forward in this article. By combining multiple sensorspsila information, the RBF neural networks extract features and estimate the running conditions, and then the adjustments of outputs are decided by fuzzy control. By using the fusion method, the running conditionspsila measurements are more accurate and reliable than that using single sensor method and the control system can adapt to the time-varying characteristic of the ball mill pulverizing system. The practical application indicates that the information fusion based control system runs stably and efficiently.

Published in:

Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on

Date of Conference:

25-27 June 2008