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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*
Department of Physics, University of Yaounde I, Yaounde, Cameroon. E-mail:
Jean Bosco Mbede
Department of Electrical and Telecommunications Engineering, Ecole Nationale Superieure Polytechnique, University of Yaounde I, Yaounde, Cameroon. E-mails:,
Achille Melingui
Department of Electrical and Telecommunications Engineering, Ecole Nationale Superieure Polytechnique, University of Yaounde I, Yaounde, Cameroon. E-mails:,
Bernard Essimbi Zobo
Department of Physics, University of Yaounde I, Yaounde, Cameroon. E-mail:
*Corresponding author. E-mail:


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.

Copyright © Cambridge University Press 2018 

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