Research on Trajectory Tracking Control of Robots in Narrow Spaces Based on Disturbance Compensation

The precise tracking of planned paths in narrow spaces has always been a research hotspot and challenge in the field of robotics. This paper proposes a model predictive control framework based on active disturbance compensation, aiming to address the interference issues caused by robot inertia and sideslip in narrow spaces. We introduce a disturbance observer to estimate disturbances and utilize a spatial decomposition method for active compensation. An MPC optimization problem is established and solved to achieve precise tracking control. Finally, simulation experiments are conducted in narrow spaces, and the results demonstrate that the improved MPC algorithm significantly outperforms the traditional MPC algorithm in terms of control performance.