Skip to main content
SpringerLink
Log in

Modelling and Control of a Non-linear Inverted Pendulum Using an Adaptive Neuro-Fuzzy Controller

  • Conference paper
  • First Online:
Recent Trends in Information and Communication Technology (IRICT 2017)

Part of the book series: Lecture Notes on Data Engineering and Communications Technologies ((LNDECT,volume 5))

  • 2431 Accesses

Abstract

The inverted pendulum system is a benchmark system for testing the performance of different control algorithms. Since it is a non-stable system, a continuously corrected mechanism is needed to move the cart in a certain way in order to balance the pendulum and prevent it from falling due to gravity. In this paper, a four-input adaptive neuro-fuzzy controller is used to control the system in a short time. The controller is implemented in MATLAB Simulink and its performance was compared with the Sugeno-type fuzzy controller. It is found that the Adaptive Neuro-fuzzy controller provides better performance as it has almost no overshoot compared to the Sugeno-type controller. Moreover, its execution time is much less than the time needed for the Sugeno-type fuzzy controller.

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

Access this chapter

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Institutional subscriptions

Similar content being viewed by others

References

  1. Ogata, K.: Modern Control Engineering, 5th edn. Prentice, Upper Saddle River (2010)

    Google Scholar 

  2. Lundberg, K.H., Barton, T.W.: History of inverted-pendulum systems. In: International Federation of Automatic Control (IFAC), vol. 42, issue 24, pp. 131–135 (2010)

    Google Scholar 

  3. Yusuf, L.A., Magaji, N.: GA-PID controller for position control of inverted pendulum. In: 6th IEEE International Conference on Adaptive Science and Technology (ICAST), pp. 1–5. IEEE Press, Ota (2014)

    Google Scholar 

  4. Bugeja, M.: Non-linear swing-up and stabilizing control of an inverted pendulum system. In: The IEEE Region 8 EUROCON 2003: Computer as a Tool, vol. 2, pp. 437–441. IEEE Press, Ljubljana (2003)

    Google Scholar 

  5. Nour, M.I.H., Ooi, J., Chan, K.Y.: Fuzzy logic control vs. conventional PID control of an inverted pendulum robot. In: International Conference on Intelligent and Advanced Systems, Kuala Lumpur, pp. 209–214 (2007)

    Google Scholar 

  6. Li, J., Gao, X., Huang, Q., Matsumoto, O.: Controller design of a two-wheeled inverted pendulum mobile robot. In: IEEE International Conference on Mechatronics and Automation, pp. 7–12. IEEE Press, Takamatsu (2008)

    Google Scholar 

  7. Jia-Jun, W.: Position and speed tracking control of inverted pendulum based on double PID controllers. In: 34th Chinese Control Conference (CCC), Hangzhou, pp. 4197–4201 (2015)

    Google Scholar 

  8. Tripathi, S.K., Panday, H., Gaur, P.: Robust control of Inverted pendulum using fuzzy logic controller. In: Students Conference on Engineering and Systems (SCES), Allahabad, pp. 1–6 (2013)

    Google Scholar 

  9. Singh, Y., Bhatotia, M., Mitra, R.: Hybrid controller for inverted pendulum. In: International Conference on Advances in Power Conversion and Energy Technologies (APCET), Mylavaram, Andhra Pradesh, pp. 1–4 (2012)

    Google Scholar 

  10. Lee, G.H., Jung, S.: Control of inverted pendulum system using a neuro-fuzzy controller for intelligent control education. In: IEEE International Conference on Mechatronics and Automation, pp. 965–970. IEEE Press, Takamatsu (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Control and Mechatronics, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, 81310, Johor Bahru, Malaysia

    Mohammed A. A. Al-Mekhalfi & Herman Wahid

Authors
  1. Mohammed A. A. Al-Mekhalfi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Herman Wahid
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Herman Wahid .

Editor information

Editors and Affiliations

  1. Faculty of Computing Information Systems Department, Universiti Teknologi Malaysia, Johar, Skudai, Malaysia

    Faisal Saeed

  2. Faculty of Computing Information Systems Department, Universiti Teknologi Malaysia, Johar, Skudai, Malaysia

    Nadhmi Gazem

  3. Department of Computer Science and Engineering, SOA University, Bhubaneswar, Odisha, India

    Srikanta Patnaik

  4. Faculty of Computing, ISSI Research Lab, University of Technology Malaysia, Skudai, Malaysia

    Ali Saleh Saed Balaid

  5. Faculty of Computing, University of Technology Malaysia, Skudai, Malaysia

    Fathey Mohammed

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this paper

Cite this paper

Al-Mekhalfi, M.A.A., Wahid, H. (2018). Modelling and Control of a Non-linear Inverted Pendulum Using an Adaptive Neuro-Fuzzy Controller. In: Saeed, F., Gazem, N., Patnaik, S., Saed Balaid, A., Mohammed, F. (eds) Recent Trends in Information and Communication Technology. IRICT 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 5. Springer, Cham. https://doi.org/10.1007/978-3-319-59427-9_24

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-59427-9_24

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-59426-2

  • Online ISBN: 978-3-319-59427-9

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation