Trajectory Tracking of Double-Joint Manipulator Based on Robust Adaptive Sliding Mode Control

Abstract

In the presence of strong coupling, nonlinear time-varying dynamics, and uncertainties such as unmodeled dynamics and external disturbances, it is challenging to establish an accurate mathematical model for a dual-joint robotic system. This leads to a degradation in tracking accuracy and affects system stability. In this paper, a robust adaptive sliding mode control algorithm is proposed for trajectory tracking of a dual-joint robotic arm to improve tracking accuracy and achieve good dynamic performance. Firstly, the dynamic equations of the dual-joint robotic arm are analyzed, considering inertia characteristics, Coriolis and centrifugal force characteristics, and gravity torque characteristics. A sliding function is constructed to approximate the unknown variables of the robotic arm, and a robust adaptive law is used to adjust the unknowns for stability and ensure tracking accuracy. Secondly, the stability analysis based on Lyapunov stability theory demonstrates that the proposed control algorithm enables the system to quickly track the desired trajectory and eventually achieve asymptotic stability. Finally, numerical simulations are conducted to validate the effectiveness of the proposed algorithm.