Minimum Entropy Control for Stochastic Systems Based on the Wavelet Neural Networks

  • Chengzhi Yang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


The main idea of this paper is to characterize the uncertainties of control system base upon entropy concept. The wavelet neural networks is used to approach the nonlinear system through minimizing Renyi’s entropy criterion of the system estimated error, and the controller design is based upon minimizing Renyi’s entropy criterion of the system tracking errors. An illustrative example is utilized to demonstrate the effectiveness of this control solution, and satisfactory results have been obtained.


Wavelet Neural Network Control System Base System Estimate Error Unknown Probability Density Nonlinear Dynamic Stochastic System 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chengzhi Yang
    • 1
  1. 1.Kunming University of Science and TechnologyChina

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