Vol. 20 No. 4 (2017) Cover Image
Vol. 20 No. 4 (2017)

Published: August 31, 2017

Pages: 853-863

Articles

Adaptive Control of Robot Manipulators with Velocity Estimation and Bounded Torque

Abstract

The robot manipulator output feedback problem points out to the controlled system in which the measurements of the joint position are available. In this study, all kinematic and dynamic parameters of robot manipulator are supposed unknown and the manipulator have to follow the desired trajectory. Therefore, the adaptive control problem for robot manipulators based on velocity estimation is investigated. According to the practical robot actuator power limitation, the bounded torque input is also considered in this study. The control algorithm is applied for 2-link manipulator to evaluate controller effectiveness. The design parameters that guaranteed the control performance of closed loop system are chosen by using optimization output constrained method. The proposed controller performances are provided by numerical simulations.

References

  1. Burg T., Dawson D. and Vedagarbha P., 1997,A redesigned DCAL controller without velocity measurements: theory and demonstration”, Robotica, Vol. 15, pp. 337–346.
  2. F. Zhang, D.M. Dawson, M.S. de Queiroz and W. Dixon, 2000, Global adaptive output feedback tracking control of robot manipulators, IEEE Transactions on Automatic Control, Vol. 45, No.6 pp. 1203– 1208.
  3. Zergeroglu E., Dawson D. M., de Queiroz M.S., and Krstic M., 2000, On Global Output Feedback Tracking Control of Robot Manipulators, Proc. of the IEEE Conference on Decision and Control, Sydney, Australia, pp. 5073-5078.
  4. Arteaga, M. A., 2003,“Robot control and parameter estimation with only joint position measurements”, Automatica, Vol. 39, pp. 67–73.
  5. Craig J. J., Hsu P., and Sastry S. S., 1987, “Adaptive control of mechanical manipulators,” The International Journal of Robotics Research, vol. 6, no. 2, pp. 16–28.
  6. Slotine J.-J. E. and Li W., 1987, “On the adaptive control of robot manipulators,” The International Journal of Robotics Research, vol. 6, no. 3, pp. 49–59.
  7. Middleton R. H. and Goodwin G. C., 1988, “Adaptive computed torque control for rigid link manipulators,” Systems & Control Letters, vol. 10, no. 1, pp. 9–16.
  8. Li P., Ma J. and Zheng Z.,2016,Robust adaptive sliding mode control for uncertain nonlinear MIMO system with guaranteed steady state tracking error bounds, Journal of the Franklin Institute, Vol. 353,2, pp. 303-321.
  9. Lor A. and iacute, 2016, Observers are Unnecessary for Output-Feedback Control of Lagrangian Systems, IEEE Transactions on Automatic Control, Vol. 61,4, pp. 905-920.
  10. Wang J. P., Yangjun M., Hu J., Yumei A., Gong N. And Xiansheng B., 2015, A Novel Fuzzy Optimal Controller on Motion and Vibration Coordination Control for a Multi-flexible Link Manipulator, The 14th IFToMM World Congress, Taipei, Taiwan.
  11. Tran T.-T., Ge S. S. and He W., 2016,Adaptive control for an uncertain robotic manipulator with input saturations, Control Theory and Technology, Vol. 14,2, pp. 113-121.
  12. Cho S. J., et al., 2016, Adaptive time-delay control with a supervising switching technique for robot manipulators, Transactions of the Institute of Measurement and Control, March 31.
  13. He W., Dong Y. and Sun C., 2016,Adaptive Neural Impedance Control of a Robotic Manipulator With Input Saturation,I EEE Transactions on Systems, Man, and Cybernetics: Systems, Vol. 46,3, pp. 334-344.
  14. Zavala-Río A., Mendoza M., Santibáñez V. , and Reyes F., 2015, Output-Feedback PID-type Global Regulator for Robot Manipulators with Bounded Inputs, Mexico, IFAC-Papers OnLine, Vol. 48,19, pp. 87-93.
  15. Li Y., Tong S. and Li T., 2013, Adaptive fuzzy output feedback control for a single-link flexible robot manipulator driven DC motor via backstepping, Nonlinear Analysis: Real World Applications, Vol. 14,1, pp. 483-494.
  16. SuY. and ZhengC.,2010, Vision-based PID regulation of robotic manipulators without velocity measurements, Robotics and Biomimetics (ROBIO), 2010 IEEE International Conference on, pp. 1698-1703.
  17. Belanger P. R.,1992, Estimation of angular velocity and acceleration from shaft encoder measurements, Robotics and Automation, 1992. Proceedings., 1992 IEEE International Conference on,vol.581, pp. 585-592.
  18. Lewis F., Abdallah C., and DawsonD.,1993, Control of Robot Manipulators, New York, MacMillan.
  19. Sciavicco L. andSicilianoB.,200, Modeling and control of robot manipulators, Springer, London.
  20. Canudas de Wit C., Siciliano B. And Bastin G. (eds.), 1996, Theory of robot control, Springer-Verlag, London.
  21. Spong M. W., Hutchinson S., and Vidyasagar M., 2006, Robot Modeling and Control. New York: Wiley.
  22. ArimotoS.,1995, Fundamental problems of robot control: Part I, Innovations in the realm of robot servo-loops, Robotica, Vol. 13,01, pp. 19-27.
  23. ArimotoS.,1995, Fundamental problems of robot control: Part II A nonlinear circuit theory towards an understanding of dexterous motions, Robotica, Vol. 13,02, pp. 111-122.
  24. Kelly R. and Salgado R., 1994, PD control with computed feed forward of robot manipulators: a design procedure, IEEE Transactions on Robotics and Automation, Vol. 10,4, pp. 566-571.
  25. Santibanez V. and KellyR.,2001, PD control with feedforward compensation for robot manipulators: analysis and experimentation, Robotica, Vol. 19,1, pp. 11-19.