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A regressor-free adaptive controller for robot manipulators without Slotine and Li's modification

Published online by Cambridge University Press:  01 May 2013

Chen-Yu Kai  and
An-Chyau Huang
Chen-Yu Kai*
Affiliation:
Department of Mechanical Engineering, National Taiwan University of Science and Technology, No. 43, Keelung Rd., Sec. 4, Taipei 10607, Taiwan, Republic of China. E-mail: [email protected]
An-Chyau Huang
Affiliation:
Department of Mechanical Engineering, National Taiwan University of Science and Technology, No. 43, Keelung Rd., Sec. 4, Taipei 10607, Taiwan, Republic of China. E-mail: [email protected]
*
*Corresponding author. E-mail: [email protected]
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Summary

Similar to the traditional adaptive strategies for robot manipulators, the regressor-free adaptive controller design also requires applying Slotine and Li's modification to avoid the feedback of joint accelerations. In this paper, a simple method is proposed to construct a regressor-free adaptive controller for robot manipulators without Slotine and Li's modification. In the new design, the joint acceleration vector is lumped into an unknown time-varying function and the function approximation technique is utilized to cover its effect; therefore, its implementation is free from joint acceleration feedback. The closed-loop stability and boundedness of internal signals are justified by the Lyapunov-like technique. Both simulation and experimental results for a two-link robot are presented to show the effectiveness of the proposed design.

Keywords

RobotAdaptive controlFunction approximation technique (FAT)
Type
Articles
Information
Robotica , Volume 31 , Issue 7 , October 2013 , pp. 1051 - 1058
Copyright
Copyright © Cambridge University Press 2013 

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References

1.Jezernik, K., Rodic, M., Safaric, R. and Curk, B., “Neural network sliding mode robot control,” Robotica 15, 23–30 (2000).CrossRefGoogle Scholar
2.Ge, S. S., Hang, C. C., Lee, T. H. and Zang, T., Stable Adaptive Neural Network Control (Kluwer, Norwell, MA, 2001).Google Scholar
3.Topalov, A. V., Kaynak, O. and Aydin, G., “Neuro-adaptive sliding-mode tracking control of robot manipulators,” Int. J. Adapt. Control Signal Process. 21, 674–691 (2007).CrossRefGoogle Scholar
4.Jung, S. and Hsia, T. C., “Neural network impedance force control of robot manipulator,” IEEE Trans. Ind. Electron. 45 (3), 451–461 (1998).CrossRefGoogle Scholar
5.Achili, B., Daachi, B., Amirat, Y., Ali-Cherif, A. and Daachi, M. E., “A stable adaptive force/position controller for a C5 parallel robot: A neural network approach,” Robotica 30, 1177–1187 (2012).CrossRefGoogle Scholar
6.Ortega, R. and Spong, M. W., “Adaptive motion control of rigid robots: A tutorial,” Automatica 25 (6), 877–888 (1989).CrossRefGoogle Scholar
7.Craig, J. J., Hsu, P. and Sastry, S. S., “Adaptive Control of Mechanical Manipulators,” Proceedings of the IEEE International Conference on Robotics and Automation, San Francisco, California (1986) pp. 190–195.Google Scholar
8.Hsu, P., Bodson, M., Sasiry, S. S. and Paden, B., “Adaptive Identification and Control for Manipulators Without Using Joint Accelerations,” Proceedings of the International Conference on Robotics and Automation (1987) pp. 1210–1215.Google Scholar
9.Middleton, R. H. and Goodwin, G. C., “Adaptive computed torque control for rigid link manipulations,” Syst. Control Lett. 10, 9–16 (1988).CrossRefGoogle Scholar
10.Kelly, R., “Adaptive computed torque plus compensation control for robot manipulators,” Mech. Mach. Theory 25 (2), 161–165 (1990).CrossRefGoogle Scholar
11.Slotine, J.-J. E. and Li, W. P. “On the adaptive control of robot manipulators,” Int. J. Robot. 6 (3), 49–59 (1987).CrossRefGoogle Scholar
12.Hsia, T. C., Lasky, T. A. and Guo, Z., “Robust independent joint controller design for industrial robot manipulators,” IEEE Trans. Ind. Electron. 38, 21–25 (1991).CrossRefGoogle Scholar
13.Song, Y. D., “Adaptive motion tracking control of robot manipulators—non-regressor based approach,” Int. J. Control 63 (1), 41–54 (1996).CrossRefGoogle Scholar
14.Su, C. Y. and Stepanenko, Y., “Adaptive Control for Constrained Robots Without Using Regressor,” Proceeding of the IEEE International Conference on Robotics and Automation (1996) pp. 264–269.Google Scholar
15.Huang, A. C., Wu, S. C. and Ting, W. F., “An FAT-based adaptive controller for robot manipulators without regressor matrix: Theory and experiments,” Robotica 24, 205–210 (2006).CrossRefGoogle Scholar
16.Huang, A. C. and Chien, M. C., Adaptive Control of Robot Manipulators – A Unified Regressor-free Approach (World Scientific Publishing, Singapore, 2010).CrossRefGoogle Scholar
17.Chein, M. C. and Huang, A. C., “Adaptive impedance controller design for flexible-joint electrically-driven robots without computation of the regressor matrix,” Robotica 30, 133–144 (2012).CrossRefGoogle Scholar