Active Disturbance Rejection Predictive Control for Drill-Arm Positioning of Hydraulic Drill-Anchor Robots Based on Friction Compensation and PSO Tuning

The anchoring effect of drill-anchor equipment directly determines the support quality of roadways. Currently, hydraulic drill-anchor robots suffer from insufficient positioning control precision during operation, and drilling position deviations induce roadway collapse risks and serious safety hazards. Therefore, effectively improving the position control accuracy of the drill arm of drill-anchor robots is a critical prerequisite for ensuring roadway support safety. Aiming at the drill-arm position control system of drill-anchor robots, this study establishes a friction model for friction compensation based on the analysis of the motion mechanism of drill-anchor robots and then constructs mathematical models for the slewing and pitching systems respectively. To realize the precise position control of the drill arm, an active disturbance rejection predictive control scheme is proposed. An extended state observer (ESO) is adopted to observe the system states and unmodeled disturbances, and the particle swarm optimization (PSO) algorithm with an improved objective function is applied to optimize the parameters of the drill-arm position controller. Finally, simulation results demonstrate that the designed active disturbance rejection predictive control method for drill-arm positioning, based on friction compensation and PSO tuning, exhibits excellent control performance and achieves accurate trajectory tracking of the drill-arm position of drill-anchor robots. This research has important theoretical and practical significance for promoting the automatic control of drill-anchor robots in underground engineering.