吉林大学学报(工学版) ›› 2003, Vol. ›› Issue (3): 51-54.

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Complex system control strategy based on a novel CMAC-type neural network

WANG Jun-song1, WANG Shu-zhen2   

  1. 1. Department of Automation Engineering, Tianjin University of Technology and Education, Tianjin 300222, China;
    2.Tianjing Dagang Oil Field, Tianjin 300280, China
  • Received:2003-01-04

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Abstract: On the basis of discrete Taylor series,this paper proposes a novel CMAC neural networkor (DTS CMAC), including an interpolation algorithm and a training algorithm, which is capable of implementing error free approximations to multi variable polynomial functions of arbitrary order. The network offers several advantages such as high learning precision and much smaller memory requirement without data collision problem compared to the conventional CMAC-type neural network.Based on DTS CMAC,a complex on line system control strategy with high performance,independent on system mathematic model,robust,and universal is designed.Simulation results verify that this proposed control strategy is both feasible and efficient.

Key words: Discrete Taylor Series, neural network, complex system control

CLC Number: 

  • TP273
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