Share This Article:

An Adaptive Fuzzy Controller for Trajectory Tracking of Robot Manipulator

Abstract Full-Text HTML Download Download as PDF (Size:376KB) PP. 364-370
DOI: 10.4236/ica.2011.24041    4,717 Downloads   7,648 Views   Citations


In this paper, an adaptive fuzzy control algorithm is proposed for trajectory tracking of an n-DOF robot manipulator subjected to parametric uncertainty and it is advantageous compared to the conventional nonlinear saturation controller. The asymptotic stability of the proposed controller has been derived based on Lyapunaov energy function. The design procedure is straightforward due to its simple fuzzy rules and control strategies. The simulation results show that the present control strategy effectively reduces the control effort with negligible chattering in control torque signals in comparison to the existing nonlinear saturation controller.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

A. Khalate, G. Leena and G. Ray, "An Adaptive Fuzzy Controller for Trajectory Tracking of Robot Manipulator," Intelligent Control and Automation, Vol. 2 No. 4, 2011, pp. 364-370. doi: 10.4236/ica.2011.24041.


[1] J. J. E. Slotine and W. Li, “On the Adaptive Control of Robotic Manipulators,” International Journal of Robotics Research, Vol. 6, No. 3, 1987, pp. 49-59. doi:10.1177/027836498700600303
[2] M. W. Spong, “On the Robust Control of Robot Manipulators,” IEEE Transactions on Automatic Control, Vol. 37, No. 11, 1992, pp. 1782-1786. doi:10.1109/9.173151
[3] A. B. Sharkawy, M. M. Othman and A. M. A. Khalil, “A Robust Fuzzy Tracking Control Scheme for Robotic Manipulators with Experimental Verification,” Intelligent Control and Automation, Vol. 2, No. 2, 2011, pp. 100-111. doi:10.4236/ica.2011.22012
[4] M. Galicki, “An Adaptive Regulator of Robotic Manipulators in the Task Space,” IEEE Transactions on Automatic Control, Vol. 53, No. 4, 2008, pp. 1058-1062. doi:10.1109/TAC.2008.921022
[5] M. W. Spong, S. Hutchinson and M. Vidyasagar, “Robot Modeling and Control,” John Wiley & Sons Inc., New York, 2006.
[6] C. C. Cheah, C. Liu and J. J. E. Soltine, “Adaptive Tracking Control for Robots with Unknown Kinematics and Dynamic Uncertainty,” International Journal of Robotics Research, Vol. 25, No. 3, 2006, pp. 283-296. doi:10.1177/0278364906063830
[7] T. H. S. Li and Y. C. Huang, “MIMO Adaptive Fuzzy Terminal Sliding-Mode Controller for Robotic Manipulators,” Information Sciences, Vol. 180, No. 23, 2010, pp. 4641-4660. doi:10.1016/j.ins.2010.08.009
[8] Z. Bingul and O. karahan, “A Fuzzy Logic Controller Tuned with PSO for 2 DOF Robot Trajectory Control,” Expert Systems with Applications, Vol. 38, No. 1, 2011, pp. 1017-1031. doi:10.1016/j.eswa.2010.07.131
[9] L.-X. Wang, “Stable Adaptive Fuzzy Control of Nonlinear Systems,” IEEE Transactions on Fuzzy Systems, Vol. 1, No. 2, 1993, pp. 146-155.
[10] G. Feng, “A Survey on Analysis and Design of Model-Based Fuzzy Control Systems,” IEEE Transactions on Fuzzy Systems, Vol. 14, No. 5, 2006, pp. 676-697.
[11] M. W. Spong and M. Vidyasagar, “Robot Dynamics and Control,” Wiely, New York, 1989.
[12] L. X. Wang, “A Course in Fuzzy Systems and Control,” Prentice-Hall, Englewood Cliffs, 1997.

comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.