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An Improved BP Algorithm Based on Global Revision Factor and Its Application to PID Control

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Advances in Neural Networks - ISNN 2006 (ISNN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3972))

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Abstract

To improve BP algorithm in overcoming the local minimum problem and accelerating the convergence speed, a new improved algorithm based on global revision factor of BP neural network is presented in this paper. The basic principle is to improve the formula of weight adjusting used momentum back propagation. A global revision factor is added in the weight value adjusting formula of momentum BP. Faster learning speed is obtained by adaptive adjusting this factor. The new BP algorithm is compared with other improved BP algorithms on many aspects. Simulation and applications for complex nonlinear function approximation, neural PID parameter tuning indicates that it has better training speed and precision than momentum back propagation and adaptive learning rate.

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Author information

Authors and Affiliations

  1. School of Automation and Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China

    Lin Lei, Houjun Wang & Yufang Cheng

Authors
  1. Lin Lei
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  2. Houjun Wang
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  3. Yufang Cheng
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

  3. Department of Electrical Engineering, University of Louisville, 40292, Louisville, KY, U.S.A

    Jacek M. Zurada

  4. Laboratory for Computational Biology, Shanghai Center for Systems Biomedicine, 800 Dong Chuan Rd., 200240, Shanghai, China

    Bao-Liang Lu

  5. School of Electrical and Electronic Engineering, University of Manchester, UK

    Hujun Yin

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© 2006 Springer-Verlag Berlin Heidelberg

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Lei, L., Wang, H., Cheng, Y. (2006). An Improved BP Algorithm Based on Global Revision Factor and Its Application to PID Control. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3972. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760023_150

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  • DOI: https://doi.org/10.1007/11760023_150

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34437-7

  • Online ISBN: 978-3-540-34438-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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