Disturbance Observer-based Trajectory Following Control of Robot Manipulators

  • Mohamadreza HomayounzadeEmail author
  • Amir Khademhosseini
Regular Papers Robot and Applications


Robotic manipulators are usually subject to different types of disturbances. If the effects of such disturbances are not taken into account, it can lead to unsatisfactory tracking performance of the robot and may even destabilize the robot control system. In this paper a novel nonlinear disturbance observer-based controller is designed for robotic manipulators. Previous disturbance observer-based controllers which are designed for robotic systems undergo the restricting assumption that the external disturbance is constant. In this paper a novel two-stage procedure is proposed to design a disturbance observer that improves disturbance attenuation ability of current disturbance observer-based controllers. The proposed method can cope with non-constant disturbance. Furthermore, it is shown that even for the fast time varying disturbance, the controller achieves satisfactory tracking performance. The proposed controller guarantees semi-global asymptotic position and velocity tracking and moreover, removes restrictions of previous studies on the number of degrees of freedom (DOFs), joint types, and manipulator configuration. The effectiveness of the proposed method is verified against different types of external disturbance applied on the robot manipulator and the results are compared with the results of previous methods. Furthermore, the results support the theoretical conclusions.


Disturbance observer robotic manipulators stability analysis time varying disturbance trajectory following 


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  1. [1]
    S. Li, J. Yang, W. H. Chen, and X. Chen, Disturbance Observer–Based Control: Methods and Applications, CRC, Boca Raton, FL, April 2014.Google Scholar
  2. [2]
    C. H. Choi and N. Kwak, “Robust control of robot manipulator by model–based disturbance attenuation,” IEEE/ASME Trans. on Mechatronics, vol. 8, no. 4, pp. 511–513, December 2003.CrossRefGoogle Scholar
  3. [3]
    C. Zhongyi, S. Fuchun, and C. Jing, “Disturbance observer–based robust control of free–floating space manipulators,” IEEE Systems Journal, vol. 2, no. 1, pp.114–119, March 2008.CrossRefGoogle Scholar
  4. [4]
    J. H. She, M. Fang, Y. Ohyama, H. Hashimoto, and M. Wu, “Improving disturbance–rejection performance based on an equivalent–input–disturbance approach,” IEEE Trans. on Industrial Electronics, vol. 55, no. 1, pp. 380–389, January 2008.CrossRefGoogle Scholar
  5. [5]
    B. Bona and M. Indri, “Friction compensation in robotics: an overview,” Proc. of 44th IEEE Conf. on Decision and Control, pp. 4360.4367, 2005.CrossRefGoogle Scholar
  6. [6]
    U. Sawut, N. Umeda, K. B. Park, T. Hanamoto, and T. Tsuji, “Frictionless control of robot arm with sliding mode observer,” Proc. of the IEEE International Vehicle Electronics Conf., pp. 61–66, 2001.Google Scholar
  7. [7]
    Z. J. Yang, Y. Fukushima, and P. Qin, “Decentralized adaptive robust control of robot manipulators using disturbance observers,” IEEE Trans. on Control Systems Technology, vol. 20, no. 5, pp.1357–1365, September 2012.CrossRefGoogle Scholar
  8. [8]
    Y. X. Su, B. Y. Duan, C. H. Zheng, Y. F. Zhang, G. D. Chen, and J. W. Mi, “Disturbance–rejection high–precision motion control of a Stewart platform,” IEEE Trans. on Control Systems Technology, vol. 12, no. 3, pp. 364–374, May 2004.CrossRefGoogle Scholar
  9. [9]
    A. Mohammadi, H. J. Marquez, and M. Tavakoli, “Disturbance observer–based trajectory following control of nonlinear robotic manipulators,” Proc. of the 23rd CANCAM, pp. 5–9, 2011.Google Scholar
  10. [10]
    A. Mohammadi, M. Tavakoli, H. J. Marquez, and F. Hashemzadeh, “Nonlinear disturbance observer design for robotic manipulators,” Control Engineering Practice, vol. 21, no. 3, pp. 253–267, March 2013.CrossRefGoogle Scholar
  11. [11]
    S. Katsura, Y. Matsumoto, and K. Ohnishi, “Modeling of force sensing and validation of disturbance observer for force control,” IEEE Trans. on Industrial Electronics, vol. 54, no. 1, pp. 530–538, February 2007.CrossRefGoogle Scholar
  12. [12]
    M. Rakotondrabe, C. Clévy, K. Rabenorosoa, and K. Ncir, “Force estimation and control of an instrumented platform dedicated to automated micromanipulation tasks,” Proc. of IEEE Conf. on Automation Science and Engineering, pp. 722–727, 2010.Google Scholar
  13. [13]
    S. Katsura, Y. Matsumoto, and K. Ohnishi, “Analysis and experimental validation of force bandwidth for force control,” IEEE Trans. on Industrial Electronics, vol. 53, no. 3, pp. 922–928, June 2006.CrossRefGoogle Scholar
  14. [14]
    Y. Ohba, M. Sazawa, K. Ohishi, T. Asai, K. Majima, Y. Yoshizawa, and K. Kageyama, “Sensorless force control for injection molding machine using reaction torque observer considering torsion phenomenon,” IEEE Trans. on Industrial Electronics, vol. 56, no. 8, pp. 2955–2960, August 2009.CrossRefGoogle Scholar
  15. [15]
    E. Sariyildiz and K. Ohnishi, “An adaptive reaction force observer design,” IEEE/ASME Trans. on Mechatronics, vol. 20, no. 2, pp. 750–760, April 2015.CrossRefGoogle Scholar
  16. [16]
    A. Mohammadi, H. J. Marquez, and M. Tavakoli, “Nonlinear disturbance observers: design and applications to Euler–Lagrange systems,” IEEE Control Systems, vol. 37, no. 4, pp. 50–72, August 2017.MathSciNetCrossRefGoogle Scholar
  17. [17]
    M. Chen and W. H. Chen, “Disturbance–observer–based robust control for time delay uncertain systems,” International Journal of Control, Automation, and Systems, vol. 8, no. 2, pp. 445, April 2010.CrossRefGoogle Scholar
  18. [18]
    K. Kong and M. Tomizuka, “Nominal model manipulation for enhancement of stability robustness for disturbance observer–based control systems,” International Journal of Control, Automation and Systems, vol. 11, no. 1, pp. 12–20, February 2013.CrossRefGoogle Scholar
  19. [19]
    E. Kim, “A fuzzy disturbance observer and its application to control,” IEEE Transactions on Fuzzy Systems, vol. 10, no. 1, pp.77–84, February 2002.CrossRefGoogle Scholar
  20. [20]
    B. K. Kim and W. K. Chung, “Advanced disturbance observer design for mechanical positioning systems,” IEEE Trans. on Industrial Electronics, vol. 50, no. 6, pp. 1207–1216, December 2003.CrossRefGoogle Scholar
  21. [21]
    S. Komada, N. Machii, and T. Hori, “Control of redundant manipulators considering order of disturbance observer,” IEEE Trans. on Industrial Electronics, vol. 47, no. 2, pp. 413–420, April 2000.CrossRefGoogle Scholar
  22. [22]
    W. H. Chen, D. J. Ballance, P. J. Gawthrop, and J. O’Reilly, “A nonlinear disturbance observer for robotic manipulators,” IEEE Trans. on Industrial Electronics, vol. 47, no. 4, pp. 932–938, August 2000.CrossRefGoogle Scholar
  23. [23]
    A. Nikoobin and R. Haghighi, “Lyapunov–based nonlinear disturbance observer for serial n–link robot manipulators,” Journal of Intelligent & Robotic Systems, vol. 55, no. 2, pp. 135–153, July 2009.CrossRefzbMATHGoogle Scholar
  24. [24]
    R. Hao, J. Wang, J. Zhao, and S. Wang, “Observer–based robust control of 6–DOF parallel electrical manipulator with fast friction estimation,” IEEE Trans. on Automation. Science Engineering, vol. 13, no. 3, pp. 1399–1408, July 2016.CrossRefGoogle Scholar
  25. [25]
    J. Huang, S. Ri, L. Liu, Y. Wang, J. Kim, and G. Pak, “Nonlinear disturbance observer–based dynamic surface control of mobile wheeled inverted pendulum,” IEEE Trans. Control System Technology, vol. 23, no. 6, pp. 2400–2407, November 2015.CrossRefGoogle Scholar
  26. [26]
    Y. S. Lu and C. W. Chiu, “A stability–guaranteed integral sliding disturbance observer for systems suffering from disturbances with bounded first time derivatives,” International Journal of Control, Automation and Systems, vol. 9, no. 2, pp. 402–409, April 2011.CrossRefGoogle Scholar
  27. [27]
    T. Burg, D. Dawson, J. Hu, and M. De Queiroz, “An adaptive partial state–feedback controller for RLED robot manipulators,” IEEE Trans. on Automatic Control, vol. 41, no. 7, pp. 1024–1030, July 1996.MathSciNetCrossRefzbMATHGoogle Scholar
  28. [28]
    T. C. Lee, B. S. Chen, and Y. C. Chang, “Adaptive control of robots by linear time–varying dynamic position feedback,” International Journal of Adaptive Control and Signal Processing, vol. 10, no. 6, pp. 649–671, November 1996.MathSciNetCrossRefzbMATHGoogle Scholar
  29. [29]
    M. Homayounzade, M. Keshmiri, and M. Keshmiri, “Adaptive control of electrically–driven robot manipulators without velocity/current measurements,” Proc. of ASME International Mechanical Engineering Congress and Exposition, 2014.Google Scholar
  30. [30]
    M. Homayounzade and M. Keshmiri, “Noncertainty equivalent adaptive control of robot manipulators without velocity measurements,” Advanced Robotics, vol. 28, no. 14, pp. 983–996, July 2014.CrossRefGoogle Scholar
  31. [31]
    W. H. Chen, “Disturbance observer based control for nonlinear systems,” IEEE/ASME Transactions on Mechatronics, vol. 9, no. 4, pp.706–710, December 2004.MathSciNetCrossRefGoogle Scholar

Copyright information

© Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Mechanical EngineeringFasa UniversityFasaIran

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