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SUMMARY: The problem of finite-time tracking control for n-link flexible-joint robot manipulators is addressed. An adaptive fuzzy finite-time command-filtered backstepping control scheme is presented to solve the following problems: "explosion of terms" problem, finite-time stabilization of the closed-loop system, and the reduction of computational cost. To this end, new virtual adaptive control signals and new finite-time error compensation mechanism are constructed using inherent properties of robot manipulator systems. Based on the Lyapunov theory, the finite-time stabilization of the closed-loop system is proved. Simulation studies show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This study derives a robust adaptive control of electrically driven robot manipulators using a support vector regression (SVR)-based command filtered adaptive backstepping approach. The robot system is supposed to be subject to model uncertainties, neglected dynamics, and external disturbances. The command filtered backstepping algorithm is extended to the case of the robot manipulators. A robust term is added to the common adaptive SVR algorithm, to mitigate the effects of the SVR approximation error in the path tracking performance. The stability analysis of the closed loop system using the Lyapunov theory permits to highlight adaptation laws and to prove that all the signals in the closed loop system are bounded. Simulations show the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]