Skip to main content
SpringerLink
Log in

Optimizing a Fuzzy Equivalent Sliding Mode Control Applied to Servo Drive Systems

  • Conference paper
  • First Online:
Book cover International Joint Conference SOCO’18-CISIS’18-ICEUTE’18 (SOCO’18-CISIS’18-ICEUTE’18 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 771))

  • 1353 Accesses

Abstract

Positioning accuracy of servo drive systems is very important for tasks that require precision. From the control point of view, servo drive systems are complex due to their non-linear time-varying dynamics. Most of the control strategies applied to these systems either introduce undesirable chattering in the response or suppress it at the cost of producing large tracking errors. In this work, an equivalent sliding mode control based on fuzzy logic is applied to a servo system. The fuzzy membership functions of the switching function are optimized in order to improve the control robustness and to obtain accurate tracking at the same time. Simulation results show that this soft computing control proposal can effectively eliminate the chattering and reduce the tracking error for servo drive systems. It has been compared to conventional sliding mode control and sliding mode control with boundary layer with encouraging results.

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

References

  1. Zhang, Z., Yan, P., Hao, G.: A large range flexure-based servo system supporting precision additive manufacturing. Engineering 3(5), 708–715 (2017)

    Article  Google Scholar 

  2. Lee, H., Utkin, V.I.: Chattering suppression methods in sliding mode control systems. Annu. Rev. Control 31(2), 179–188 (2007)

    Article  Google Scholar 

  3. Sumantri, B., Uchiyama, N., Sano, S.: Least square based sliding mode control for a quad-rotor helicopter and energy saving by chattering reduction. Mech. Syst. Signal Process. 66, 769–784 (2016)

    Article  Google Scholar 

  4. Liu, X., Shan, Z., Li, Y.: Dynamic boundary layer based neural network quasi-sliding mode control for soft touching down on asteroid. Adv. Space Res. 59(8), 2173–2185 (2017)

    Article  Google Scholar 

  5. Gao, F., Pan, C., Han, Y.: Design and analysis of a new AUV’s sliding control system based on dynamic boundary layer. Chin. J. Mech. Eng. 26(1), 35–45 (2013)

    Article  Google Scholar 

  6. Chen, M., Yu, J.: Disturbance observer-based adaptive sliding mode control for near-space vehicles. Nonlinear Dyn. 82(4), 1671–1682 (2015)

    Article  MathSciNet  Google Scholar 

  7. Farhane, N., Boumhidi, I., Boumhidi, J.: Smart algorithms to control a variable speed wind turbine. Int. J. Interact. Multimedia Artif. Intell. 4(6), 88–95 (2017)

    Article  Google Scholar 

  8. Xu, B., Shi, G., Ji, W., Liu, F., Ding, S., Zhu, H.: Design of an adaptive nonsingular terminal sliding model control method for a bearingless permanent magnet synchronous motor. Trans. Inst. Meas. Control 39(12), 1821–1828 (2017)

    Article  Google Scholar 

  9. Joo, Y.H., Tien, L.Q., Duong, P.X.: Adaptive neural network second-order sliding mode control of dual arm robots. Int. J. Control Autom. Syst. 15(6), 2883–2891 (2017)

    Article  Google Scholar 

  10. Yu, J., Liu, J., Wu, Z., Fang, H.: Depth control of a bioinspired robotic dolphin based on sliding-mode fuzzy control method. IEEE Trans. Industr. Electron. 65(3), 2429–2438 (2018)

    Article  Google Scholar 

  11. Nagarale, R.M., Patre, B.M.: Composite fuzzy sliding mode control of nonlinear singularly perturbed systems. ISA Trans. 53(3), 679–689 (2014)

    Article  Google Scholar 

  12. Yoshimura, T.: Design of adaptive fuzzy backstepping sliding mode control for MIMO uncertain discrete-time nonlinear systems based on noisy measurements. J. Vib. Control 24(2), 393–406 (2018)

    Article  MathSciNet  Google Scholar 

  13. Lin, Y., Liping, F.: The equivalent sliding mode control based on fuzzy control for an electrical servo system. In: Proceedings of the 27th IEEE Chinese Control Conference, CCC 2008, Kunming, Yunnan, pp. 118–121 (2008)

    Google Scholar 

  14. Wang, J.W., Wu, Z.S.: Mechanical Engineering Control Foundation, 2nd edn. Higher Education Press, Beijing (2010)

    Google Scholar 

  15. Liu, J.K.: Matlab simulation for sliding model control. Tsinghua University Press, Beijing (2005)

    Google Scholar 

  16. Slotine, J.J., Sastry, S.S.: Tracking control of non-linear systems using sliding surfaces, with application to robot manipulators. Int. J. Control 38(2), 465–492 (1983)

    Article  Google Scholar 

  17. Zhao, W.J., Liu, J.Z.: An improved method of sliding mode control with boundary layer. Acta Simulata Systematica Sinica 17(1), 156–158 (2005)

    MathSciNet  Google Scholar 

  18. Santos, M.: An applied approach of intelligent control. Revista Iberoamericana de Automática e Informática Ind. RIAI 8(4), 283–296 (2011)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Computer Science School, University Complutense of Madrid, 28040, Madrid, Spain

    Zhengya Zhang & Matilde Santos

Authors
  1. Zhengya Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Matilde Santos
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Matilde Santos .

Editor information

Editors and Affiliations

  1. Computational Intelligence Group, University of the Basque Country, Sarriena, Vizcaya, Spain

    Manuel Graña

  2. Computational Intelligence Group, University of the Basque Country, Sarriena, Vizcaya, Spain

    José Manuel López-Guede

  3. Computational Intelligence Group, University of the Basque Country, Sarriena, Vizcaya, Spain

    Oier Etxaniz

  4. Department of Civil Engineering, University of Burgos, Burgos, Burgos, Spain

    Álvaro Herrero

  5. University of Salamanca, Salamanca, Salamanca, Spain

    José Antonio Sáez

  6. Department of Industrial Engineering, University of A Coruña, La Coruña, La Coruña, Spain

    Héctor Quintián

  7. University of Salamanca, Salamanca, Salamanca, Spain

    Emilio Corchado

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer International Publishing AG, part of Springer Nature

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Zhang, Z., Santos, M. (2019). Optimizing a Fuzzy Equivalent Sliding Mode Control Applied to Servo Drive Systems. In: Graña, M., et al. International Joint Conference SOCO’18-CISIS’18-ICEUTE’18. SOCO’18-CISIS’18-ICEUTE’18 2018. Advances in Intelligent Systems and Computing, vol 771. Springer, Cham. https://doi.org/10.1007/978-3-319-94120-2_29

Download citation

Publish with us

Policies and ethics

Search

Navigation