Skip to main content
Springer Nature Link
Log in

Compound Disturbance Observer for Flight Simulator

  • Conference paper
AsiaSim 2012 (AsiaSim 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 325))

Included in the following conference series:

Abstract

This paper presents estimation of disturbance to create a compound disturbance observer based on sliding modes. Disturbance observer(DOB) and sliding mode control are both effective methods in motion control. However, DOB is confined to nonlinear disturbance while sliding mode control(SMC) is limited by chattering phenomenon. The proposed method uses sliding mode to compensate the dynamic nonlinear equivalent disturbance and the switching gain of sliding mode, which is designed by disturbance estimation error using fuzzy mapping. The method also helps to decrease chattering with the help of DOB. The validity of the proposals is confirmed by experiments.

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
$34.99 /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
USD 29.95
Price excludes VAT (USA)
  • 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. Liu, Q., Er, L.J.: Disturbance observer based robust tracking control of high precision flight simulator. Journal of Beijing University of Aeronautics and Astronautics 29(2), 181–184 (2003)

    Google Scholar 

  2. Ohnishi, K., Shibata, M., Murakami, T.: Motion control for advanced mechatronics. IEEE/ASME Transactions on Mechatronics 1(1), 56–67 (1996)

    Article  Google Scholar 

  3. Grochmal, T.R., Lynch, A.F.: Precision tracking of a rotating shaft with magnetic bearings by nonlinear decoupled disturbance observers. IEEE Transactions on Control Systems Technology 15(6), 1112–1121 (2007)

    Article  Google Scholar 

  4. Yonggu, K., Jinwook, S., Ilhwan, N., et al.: An adaptive disturbance observer for a two-link robot manipulator. In: International Conference on Control, Automation and Systems, ICCAS 2008, pp. 141–145 (2008)

    Google Scholar 

  5. Kyung-Soo, K., Keun-Ho, R., Soohyun, K.: Disturbance observer for estimating higher order disturbances in time series expansion. IEEE Transactions on Automatic Control 55(8), 1905–1911 (2010)

    Article  Google Scholar 

  6. Wu, Y., Le, W., Tian, D.: Application of Sliding Mode Control Based on Disturbance Observer on High Performance Flight Motion Simulator. In: IEEE Inter. Conf. on Automation and Logistics, pp. 2695–2699 (2007)

    Google Scholar 

  7. Hace, A., Jezernik, K., Sabanovic, A.: SMC with Disturbance Observer for a Linear Belt Drive. IEEE Transactions on Industrial Electronics 54(6), 3402–3412 (2007)

    Article  Google Scholar 

  8. Weibing, G., Yufu, W., Homaifa, A.: Discrete-time variable structure control systems. IEEE Transactions on Industrial Electronics 42(2), 117–122 (1995)

    Article  Google Scholar 

  9. Young, K.D., Utkin, V.I., Ozguner, U.: A Control Engineer’s Guide to Sliding Mode Control. IEEE Trans. on Control System Technology 7(3), 328–342 (1999)

    Article  Google Scholar 

  10. Chen, X., Komada, S., Fukuda, T.: Design of a Nonlinear Disturbance Observer. IEEE Transactions on Industrial Electronics 47(2), 429–437 (2000)

    Article  Google Scholar 

  11. Man, Z.H., Yu, X.H., Eshraghian, K., et al.: A Robust Adaptive Sliding Mode Tracking Control Using An RBF Neural Network for Robotic Manipulators. In: Proc. of Conf. Neural Networks, pp. 2403–2408 (1995)

    Google Scholar 

  12. Panwar, V.: Asymptotic, Trajectory Tracking for a Robot Manipulator using RBF Neural Network and Adaptive Bound on Disturbances. In: Proc. of the 2rd Conf. Mechanical and Electrical Technology, pp. 156–160 (2010)

    Google Scholar 

  13. Tian, D.P., Wu, Y.J., Liu, X.D.: Synthesis methods of high precision motor servo system control. Electric Machines and Control 14(7), 66–74 (2010) (in Chinese)

    Google Scholar 

  14. Jamaludin, Z., Van Brussel, H., Swevers, J.: Friction Compensation of an XY Feed Table Using Friction-Model-Based Feedforward and Inverse-Model-Based Disturbance Observer. IEEE Transactions on Industrial Electronics 56(10), 3848–3853 (2009)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. School of Automation Science and Electrical Engineering, Beihang University, Beijing, 100191, China

    Youmin Liu & Dapeng Tian

  2. Beijing Institute of System Engineering, Beijing, 100101, China

    Yong Deng

Authors
  1. Youmin Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong Deng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Dapeng Tian
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. National CIMS Engineering Research Center, Department of Automation, Tsinghua University, 100084, Beijing, China

    Tianyuan Xiao

  2. School of Automation Science and Electrical Engineering, Beihang University, 100191, Beijing, China

    Lin Zhang

  3. School of Mechatronics Engineering and Automation, Shanghai University, 200072, Shanghai, China

    Minrui Fei

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Liu, Y., Deng, Y., Tian, D. (2012). Compound Disturbance Observer for Flight Simulator. In: Xiao, T., Zhang, L., Fei, M. (eds) AsiaSim 2012. AsiaSim 2012. Communications in Computer and Information Science, vol 325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34387-2_23

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-34387-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34386-5

  • Online ISBN: 978-3-642-34387-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics