Skip to main content
SpringerLink
Log in
Book cover

Innovations in Electrical and Electronics Engineering pp 683–691Cite as

Comparative Analysis Between Conventional and Neuro-Fuzzy Control Schemes for Speed Control of Induction Motor Drive

  • Conference paper
  • First Online:

  • 887 Accesses

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 626))

Abstract

Controlling speed of induction motor is very difficult during light load conditions because it has very poor power factor and high input surge current. As also, it is a constant speed motor. Conventional controllers have poor control performance and are unable to have smooth control of the speed for nonlinear loads. The intention of the proposed scheme is to design neuro-fuzzy control scheme for controlling the speed of highly nonlinear loads like induction motor to overcome the lacunas of conventional controllers. This project uses a combination of neural network and fuzzy logic controllers so that it has the advantages of both. Back propagation algorithm is used to remove the neuro-fuzzy trial and error complexity. To design and study the performance, MATLAB software is used.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   189.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   249.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. E.C. Shin, T.S. Park, W.H. Oh, J.Y. Yoo, A design method of PI controller for an induction motor with parameter variation, in Proceeding IEEE IECON, vol. 1, pp. 408–413 (2003)

    Google Scholar 

  2. A. Miloudi, A. Draou, Variable gain PI controller design for speed control and rotor resistance estimation of an indirect vector controlled induction machine drive, in Proceeding IEEE IECON, vol. 1, pp. 323–328 (2002)

    Google Scholar 

  3. C.M. Liaw, J.B. Wang, Y.C. Chang, A fuzzy adapted field-oriented mechanism for induction motor drive. IEEE Trans. Energy Convers. 11(1), 76–83 (1996)

    Article  Google Scholar 

  4. M.N. Uddin, T.S. Radwan, M.A. Rahman, Performances of fuzzy-logic-based indirect vector control for induction motor drive. IEEE Trans. Ind. Appl. 38(5), 1219–1225 (2002)

    Article  Google Scholar 

  5. F.-J. Lin, R.-J. Wai, Adaptive fuzzy-neural-network control for induction spindle motor drive. IEEE Trans. Energy Convers. 17(4), 507–513 (2002)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Electrical Engineering, Fabtech Technical Campus College of Engineering and Research, Sangola, India

    Shubhangi Kangale, B. Sampathkumar & N. Raut Mrunmayi

Authors
  1. Shubhangi Kangale
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. Sampathkumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. N. Raut Mrunmayi
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Guru Nanak Institutions, Hyderabad, India

    H. S. Saini

  2. Department of Electronics and Communication Engineering, Kakatiya University, Warangal, India

    T. Srinivas

  3. Department of Electrical Engineering, National Institute of Technology, Warangal, India

    D. M. Vinod Kumar

  4. Department of Electrical and Electronics Engineering, Guru Nanak Institutions, Hyderabad, India

    K. S. Chandragupta Mauryan

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kangale, S., Sampathkumar, B., Raut Mrunmayi, N. (2020). Comparative Analysis Between Conventional and Neuro-Fuzzy Control Schemes for Speed Control of Induction Motor Drive. In: Saini, H., Srinivas, T., Vinod Kumar, D., Chandragupta Mauryan, K. (eds) Innovations in Electrical and Electronics Engineering. Lecture Notes in Electrical Engineering, vol 626. Springer, Singapore. https://doi.org/10.1007/978-981-15-2256-7_62

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-2256-7_62

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2255-0

  • Online ISBN: 978-981-15-2256-7

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation