Improved extended state observer for the intelligent rail bulk cargo unloading device

The intelligent rail bulk cargo unloading device operates under complex conditions with multiple disturbances, including environmental factors, system uncertainties, and load variations. These disturbances pose significant challenges to achieving precise control and stable operation. To address these issues, this paper proposes an improved Extended State Observer (ESO) to dynamically estimate and compensate for the total disturbances affecting the system. By integrating the improved ESO into the control strategy, a robust controller is designed to enhance disturbance rejection and improve position control accuracy. The proposed method is validated through simulation experiments, demonstrating its effectiveness in suppressing disturbances, achieving smooth unloading operations, and meeting the functional requirements of the device in diverse working conditions. The results highlight the potential of the improved ESO-based control approach for ensuring the stability and precision of intelligent unloading systems.