Abstract
The control precision of the working device has always been a challenging aspect in unmanned excavator research due to the adoption of a triangular drive mode and a complex hydraulic system in the working mechanism. The article focuses on the research of autonomous control for the downward motion of a robotic arm in an unmanned excavator equipped with a regeneration valve. The study aims to achieve precise tracking of fast movement trajectories during operator manipulation, utilizing Model Predictive Control (MPC). Furthermore, the exceptional disturbance rejection capability of the MPC algorithm is demonstrated through interference application. A comprehensive model considering mechanical, hydraulic, and electrical factors is established for the excavator boom. The MPC algorithm is applied to achieve precise control over the boom descent process, providing a foundation for motion control in unmanned excavators. This article presents a theoretical analysis to elucidate the robustness principle of MPC in the descent control of uncertain dynamic arms. By incorporating real parameters, we successfully track predetermined planned paths at different speeds and validate them on a 20-ton hydraulic excavator. The results demonstrate that the MPC control algorithm accurately manipulates the boom descent motion while exhibiting excellent disturbance rejection performance. Compared to PID control algorithms, MPC offers wider target adaptability range and better disturbance rejection performance, making it suitable for rapid application in controlling working devices of unmanned excavators.