Fuzzy modeling of a medium-speed pulverizer using improved genetic algorithms

Authors:
Jian Zhang;Minrui Fei;Kang Li;Qiang Zhu
Affiliations:
Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics and Automation, Shanghai University, Shanghai, China;Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics and Automation, Shanghai University, Shanghai, China;School of Electronics, Electrical Engineering and Computer Science, Queen’s University of Belfast, Belfast, UK;Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics and Automation, Shanghai University, Shanghai, China
Venue:
ICIC'06 Proceedings of the 2006 international conference on Intelligent Computing - Volume Part I
Year:
2006

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Abstract

Based on the analysis of its operational mechanism, an improved nonlinear model is developed for a medium-speed pulverizer. This is achieved by identifying a group of constant coefficients for a set of nonlinear differential equations with the aid of an improved genetic algorithm. The main objective of this research is to convert the nonlinear model into a T-S fuzzy model composed of several linear models, enabling easy design of the control system for the pulverizer. The simulation results show a satisfactory agreement between the T-S fuzzy model response and the measured data, confirming the effectiveness of the proposed method. Moreover, the proposed modeling method can be easily applied to other nonlinear systems, given that their nonlinear differential equations are known “a priori”.