Application of sensorless high-robustness control for mining permanent magnet drums in belt conveyors

As an ideal alternative drive solution for mining belt conveyors, the torque output stability and anti-heavy-load disturbance capability of the mining Permanent Magnet Drum (PMD) are compromised by the harsh underground coal mine environment, characterized by high humidity, high dust levels, and strong vibrations, making long-term stable operation difficult to achieve. To address this, this paper employs the Extended Kalman filter (EKF) for real-time estimation of the rotor position and speed of the PMD, combined with the Recursive Least Squares with Forgetting Factor (RLS-FF) algorithm for online identification of the drum’s key electrical parameters, thereby enhancing its torque output stability and resistance to heavy-load disturbances. Simulation and experimental results indicate that under no-load conditions, the speed estimation error does not exceed ±0.63 r/min, and the rotor position error remains within ±0.007 rad. During startup, the belt speed transitions smoothly, and the output torque stabilizes at 1.1–1.2 kN·m. The method demonstrates good dynamic performance and disturbance rejection capability, effectively ensuring the stable and efficient operation of the mining belt conveyor and providing technical support for the practical underground application of mining PMDs.