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Robust adaptive command filtered control of a robotic manipulator with uncertain dynamic and joint space constraints

Published online by Cambridge University Press:  21 January 2018

Joseph Jean-Baptiste Mvogo Ahanda ,
Jean Bosco Mbede ,
Achille Melingui  and
Bernard Essimbi Zobo
Joseph Jean-Baptiste Mvogo Ahanda*
Affiliation:
Department of Physics, University of Yaounde I, Yaounde, Cameroon. E-mail: bessimb@yahoo.fr
Jean Bosco Mbede
Affiliation:
Department of Electrical and Telecommunications Engineering, Ecole Nationale Superieure Polytechnique, University of Yaounde I, Yaounde, Cameroon. E-mails: mbede@neuf.fr, achille.melingui@yahoo.fr
Achille Melingui
Affiliation:
Department of Electrical and Telecommunications Engineering, Ecole Nationale Superieure Polytechnique, University of Yaounde I, Yaounde, Cameroon. E-mails: mbede@neuf.fr, achille.melingui@yahoo.fr
Bernard Essimbi Zobo
Affiliation:
Department of Physics, University of Yaounde I, Yaounde, Cameroon. E-mail: bessimb@yahoo.fr
*
*Corresponding author. E-mail: josephjeanmvogo@yahoo.fr
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Summary

The problem of robust adaptive control of a robotic manipulator subjected to uncertain dynamics and joint space constraints is addressed in this paper. Command filters are used to overcome the time derivatives of virtual control, thus reducing the need for desired trajectory differentiations. A barrier Lyapunov function is used to deal with the joint space constraints. A robust adaptive support vector regression architecture is used to reduce filtering errors, approximation errors and handle dynamic uncertainties. The stability analysis of the closed-loop system using the Lyapunov theory permits to highlight adaptation laws and to prove that all signals of the closed-loop system are bounded. Simulations show the effectiveness of the proposed control strategy.

Keywords

Robust controlCommand filtered controlBarrier Lyapunov functionConstraintsSupport vector regressionRobotic manipulator
Type
Articles
Information
Robotica , Volume 36 , Issue 5 , May 2018 , pp. 767 - 786
Copyright
Copyright © Cambridge University Press 2018 

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