Extended High Gain Observer-Based Sliding Mode Control for an Electro-hydraulic System with a Variant Payload

  • Duc-Thien Tran
  • Tri-Cuong Do
  • Kyoung-Kwan AhnEmail author
Regular Paper


This paper presents a robust control regarding position control of an electro-hydraulic rotary actuator (EHRA) system under the presence of the lumped uncertainties such as the variant payload, the unknown friction, and the uncertain parameters. The proposed control is developed on a high order sliding mode control (HOSMC) and an extended high gain observer (EHGO). In detail, the HOSMC is derived to not only reduce the chattering effect but also guarantee the stability for the EHRA. In addition, the EHGO is used as a disturbance estimator to compensate the lumped uncertainties. Consequently, it helps to improve control performance. Furthermore, the stability and robustness of the whole system are theoretically proved by a Lyapunov approach. The proposed control is practically implemented through both the co-simulation between AMESIM and MATLAB, and the experiments. The results are compared to other controllers to exhibit the effectiveness of the proposed control with the lumped uncertainties.


Electro-hydraulic actuator High order sliding mode control Extended high gain observer Lyapunov 



This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Korean government (MEST) (NRF-2017R1A2B3004625) and partly supported by the Ministry of Trade, Industry & Energy(MOTIE, Korea) under Industrial Technology Innovation Program(No. 10067184).


  1. 1.
    Truong, D. Q., & Ahn, K. K. (2009). Force control for hydraulic load simulator using self-tuning grey predictor—fuzzy PID. Mechatronics,19(2), 233–246.Google Scholar
  2. 2.
    Kim, H. M., Park, S. H., Song, J. H., & Kim, J. S. (2010). Robust position control of electro-hydraulic actuator systems using the adaptive back-stepping control scheme. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering,224(6), 737–746.Google Scholar
  3. 3.
    Lee, S.-R., & Hong, Y.-S. (2017). A dual EHA system for the improvement of position control performance via active load compensation. International Journal of Precision Engineering and Manufacturing,18(7), 937–944.Google Scholar
  4. 4.
    Park, H.-G., Jeong, K.-H., Park, M.-K., Lee, S.-H., & Ahn, K.-K. (2018). Electro hydrostatic actuator system based on active stabilizer system for vehicular suspension systems. International Journal of Precision Engineering and Manufacturing,19(7), 993–1001.Google Scholar
  5. 5.
    Kim, J.-H., & Hong, Y.-S. (2018). Robust internal-loop compensation of pump velocity controller for precise force control of an electro-hydrostatic actuator. (in Ko). Journal of Drive and Control,15(4), 55–60.Google Scholar
  6. 6.
    Kim, J.-H., & Hong, Y.-S. (2019). Investigation of system efficiency of an electro-hydrostatic actuator with an external gear pump. (in Ko). Journal of Drive and Control,16(2), 15–21.Google Scholar
  7. 7.
    Tri, N. M., Nam, D. N. C., Park, H. G., & Ahn, K. K. (2015). Trajectory control of an electro hydraulic actuator using an iterative backstepping control scheme. Mechatronics,29, 96–102.Google Scholar
  8. 8.
    Truong, D. Q., & Ahn, K. K. (2011). “Force control for press machines using an online smart tuning fuzzy PID based on a robust extended Kalman filter. Expert Systems with Applications,38(5), 5879–5894.Google Scholar
  9. 9.
    Tri, N. M., Ba, D. X., & Ahn, K. K. (2018). A gain-adaptive intelligent nonlinear control for an electrohydraulic rotary actuator. International Journal of Precision Engineering and Manufacturing,19(5), 665–673.Google Scholar
  10. 10.
    Perron, M., Lafontaine, J. D., & Desjardins, Y. (2005). Sliding-mode control of a servomotor-pump in a position control application. In Canadian conference on electrical and computer engineering 2005 (pp. 1287–1291).Google Scholar
  11. 11.
    Lin, Y., Shi, Y., & Burton, R. (2013). Modeling and robust discrete-time sliding-mode control design for a fluid power electrohydraulic actuator (EHA) system. IEEE/ASME Transactions on Mechatronics,18(1), 1–10.Google Scholar
  12. 12.
    Ha, T. W., Jun, G. H., Nguyen, M. T., Han, S. M., Shin, J. W., & Ahn, K. K. (2017). Position control of an Electro-Hydrostatic Rotary Actuator using adaptive PID control. (in Ko). Journal of Drive and Control,14(4), 37–44.Google Scholar
  13. 13.
    Has, Z., Rahmat, M. F. A., Husain, A. R., & Ahmad, M. N. (2015). Robust precision control for a class of electro-hydraulic actuator system based on disturbance observer. International Journal of Precision Engineering and Manufacturing,16(8), 1753–1760.Google Scholar
  14. 14.
    Ahn, K. K., Nam, D. N. C., & Jin, M. (2014). Adaptive backstepping control of an electrohydraulic actuator. IEEE/ASME Transactions on Mechatronics,19(3), 987–995.Google Scholar
  15. 15.
    Jun, G. H., & Ahn, K. K. (2017). Extended-state-observer-based nonlinear servo control of an electro-hydrostatic actuator. (in Ko). Journal of Drive and Control,14(4), 61–70.Google Scholar
  16. 16.
    Levant, A. (2005). Homogeneity approach to high-order sliding mode design. Automatica,41(5), 823–830.MathSciNetzbMATHGoogle Scholar
  17. 17.
    Levant, A. (1993). “Sliding order and sliding accuracy in sliding mode control. International Journal of Control,58(6), 1247–1263.MathSciNetzbMATHGoogle Scholar
  18. 18.
    Han, J. (2009). From PID to active disturbance rejection control. IEEE Transactions on Industrial Electronics,56(3), 900–906.Google Scholar
  19. 19.
    Yao, J., Jiao, Z., & Ma, D. (2014). Extended-state-observer-based output feedback nonlinear robust control of hydraulic systems with backstepping. IEEE Transactions on Industrial Electronics,61(11), 6285–6293.Google Scholar
  20. 20.
    Yue, M., Wang, L., & Ma, T. (2017). Neural network based terminal sliding mode control for WMRs affected by an augmented ground friction with slippage effect. IEEE/CAA Journal of Automatica Sinica,4(3), 498–506.MathSciNetGoogle Scholar
  21. 21.
    Yen, V. T., Nan, W. Y., Van Cuong, P., Quynh, N. X., & Thich, V. H. (2017). Robust adaptive sliding mode control for industrial robot manipulator using fuzzy wavelet neural networks. International Journal of Control, Automation and Systems,15(6), 2930–2941.Google Scholar
  22. 22.
    Yen, V. T., Nan, W. Y., & Van Cuong, P. (2019). Robust adaptive sliding mode neural networks control for industrial robot manipulators. International Journal of Control, Automation and Systems,17(3), 783–792.Google Scholar
  23. 23.
    Tran, M.-D., & Kang, H.-J. (2016). A novel adaptive finite-time tracking control for robotic manipulators using nonsingular terminal sliding mode and RBF neural networks. International Journal of Precision Engineering and Manufacturing,17(7), 863–870.Google Scholar
  24. 24.
    Liang, X., Li, S., & Fei, J. (2016). Adaptive fuzzy global fast terminal sliding mode control for microgyroscope system. IEEE Access,4, 9681–9688.Google Scholar
  25. 25.
    Wang, W., Lv, F., & Zhang, L. (2018). Adaptive fuzzy finite-time control for uncertain nonlinear systems with dead-zone input. International Journal of Control, Automation and Systems,16(5), 2549–2558.Google Scholar
  26. 26.
    Cui, R., Chen, L., Yang, C., & Chen, M. (2017). Extended state observer-based integral sliding mode control for an underwater robot with unknown disturbances and uncertain nonlinearities. IEEE Transactions on Industrial Electronics,64(8), 6785–6795.Google Scholar
  27. 27.
    Khalil, H. K. (2017). Extended high-gain observers as disturbance estimators. SICE Journal of Control, Measurement, and System Integration,10(3), 125–134.Google Scholar
  28. 28.
    Heredia, J. A., & Wen, Y. (2000). A high-gain observer-based PD control for robot manipulator. In Proceedings of the 2000 American control conference. ACC (IEEE Cat. No. 00CH36334) (Vol. 4, pp. 2518–2522).Google Scholar
  29. 29.
    Ramírez-Neria, M., Sira-Ramírez, H., Garrido-Moctezuma, R., & Luviano-Juárez, A. (2019). Active disturbance rejection control of the inertia wheel pendulum through a tangent linearization approach. International Journal of Control, Automation and Systems,17(1), 18–28.Google Scholar
  30. 30.
    Chen, H.-T., Song, S.-M., & Zhu, Z.-B. (2018). Robust finite-time attitude tracking control of rigid spacecraft under actuator saturation. International Journal of Control, Automation and Systems,16(1), 1–15.Google Scholar
  31. 31.
    Wang, C., Jiao, Z., Wu, S., & Shang, Y. (2014). Nonlinear adaptive torque control of electro-hydraulic load system with external active motion disturbance. Mechatronics,24(1), 32–40.Google Scholar
  32. 32.
    Manring, N. (2005). Hydraulic control systems. New York: Wiley.Google Scholar
  33. 33.
    Khalil, H. K. (2008). High-gain observers in nonlinear feedback control. In 2008 International conference on control, automation and systems (pp. xlvii–lvii).Google Scholar
  34. 34.
    Khalil, H. K. (1996). Nonlinear systems. Upper Saddle River, NJ: Prentice-Hall.Google Scholar

Copyright information

© Korean Society for Precision Engineering 2019

Authors and Affiliations

  1. 1.School of Mechanical EngineeringUniversity of UlsanUlsanKorea

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