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Fuzzy Modeling of a Medium-Speed Pulverizer Using Improved Genetic Algorithms

  • Jian Zhang
  • Minrui Fei
  • Kang Li
  • Qiang Zhu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4113)

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”.

Keywords

Fuzzy Model Nonlinear Differential Equation Static Output Feedback Improve Genetic Algorithm Nonlinear Dynamic Characteristic 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jian Zhang
    • 1
  • Minrui Fei
    • 1
  • Kang Li
    • 2
  • Qiang Zhu
    • 1
  1. 1.Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics and AutomationShanghai UniversityShanghaiChina
  2. 2.School of Electronics, Electrical Engineering and Computer ScienceQueen’s University of BelfastBelfastUK

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