Adaptive Robust Control for Euler-Lagrange Dynamic Systems: Application with Planar Robot Arm Motion Control

In this paper, we propose a novel controller design approach for a planar robot arm. The objective is to develop an adaptive robust control (ADRC) algorithm that enhances the trajectory-tracking performance of an Euler–Lagrange dynamic system operating under uncertain conditions. In the ADRC design, the dynamic system is partitioned into two components: one with fixed but unknown parameters and another with parameters that are bounded within known limits. To mitigate performance degradation caused by time-varying parameters, a sliding-mode control element is incorporated into the adaptive control framework. This hybrid design, referred to as the ADRC, leverages the robustness of sliding-mode control and the adaptability of conventional adaptive control. The stability of the closed-loop system is established using Lyapunov's direct method. The proposed ADRC is validated through computational studies of trajectory tracking for a planar robot arm. Comparative analyses with traditional adaptive control and conventional sliding-mode control demonstrate that the ADRC achieves superior tracking accuracy and robustness while maintaining comparable control input effort. These results confirm the effectiveness of the ADRC in addressing uncertainties and parameter variations, thereby offering practical insights for advanced motion control in robotic systems.