[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content
Springer Nature Link
Log in

Genetic Algorithm Based Neuro-fuzzy Network Adaptive PID Control and Its Applications

  • Conference paper
Computational and Information Science (CIS 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3314))

Included in the following conference series:

Abstract

It is difficult to satisfy most of the performance targets by using the PID control law only, if the plants are the processes with uncertain time-delay, varying parameters and non-linearity. For this reason a genetic algorithm based neuro-fuzzy network adaptive PID controller is proposed in this paper. The neuro-fuzzy network is used to amend the parameters of the PID controller online, the global optimal parameters of the network are found with a high speed, and the improved genetic algorithm is introduced to overcome the local optimum defect of the BP algorithm. Finally, the simulation experiment of the control method on the tobacco-drying control process is performed. The simulation results demonstrate that this kind of control method is effective.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 88.50
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Feng, D., Xie, S.: Fuzzy and Intelligence Control. The Publishing of Chemical Industry (1998)

    Google Scholar 

  2. Li, S.: Intelligence Control Theory and Application. The Publishing of Ha Er Bi Bin University (1996)

    Google Scholar 

  3. Chen, J.: Tobacco-drying Intelligence Control System, vol. 6. Kun Ming University of Science and Technology (2001)

    Google Scholar 

  4. Chen, G., Wang, X.: Genetic Algorithm and Application. The Publishing of Ren Min Post Office (1996)

    Google Scholar 

  5. Baker, Z.: Adaptive Selection Methods for Genetic Algorithms. In: Proc. 1st Int’l. Conf. on Genetic Algorithms, pp. 110–111. Lawrence Earlbaum Associates, Hilladale (1985)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Mechatronical Engineering and Automation, Shanghai University, 200072, Shanghai, China

    Dongqing Feng & Minrui Fei

  2. Institute of Information and Control, Zhengzhou University, 450002, Zhengzhou, China

    Dongqing Feng, Lingjiao Dong & Tiejun Chen

Authors
  1. Dongqing Feng
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Lingjiao Dong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Minrui Fei
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tiejun Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Electronic Science and Technology, Anhui University, Hefei, Anhui, China

    Jun Zhang

  2. College of Science, Donghua University, 1882 Yan’an Xilu Road, 20051, Shanghai, China

    Ji-Huan He

  3. BASICS, Department of Computer Science and Engineering, Shanghai Jiao Tong University, 200030, Shanghai, China

    Yuxi Fu

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Feng, D., Dong, L., Fei, M., Chen, T. (2004). Genetic Algorithm Based Neuro-fuzzy Network Adaptive PID Control and Its Applications. In: Zhang, J., He, JH., Fu, Y. (eds) Computational and Information Science. CIS 2004. Lecture Notes in Computer Science, vol 3314. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30497-5_52

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30497-5_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24127-0

  • Online ISBN: 978-3-540-30497-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation