Minimum Entropy Control for Stochastic Systems Based on the Wavelet Neural Networks
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.
KeywordsWavelet Neural Network Control System Base System Estimate Error Unknown Probability Density Nonlinear Dynamic Stochastic System
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