Predictive Control of Cranes Based on Disturbance Compensation

To solve the problem of insufficient robustness and constraint in the positioning control of overhead cranes, an improved model predictive control scheme combined with disturbance compensation is proposed. Firstly, a mathematical model of the overhead crane is established, and disturbances are estimated using an extended state observer. Next, the estimated disturbance values are compensated in the predictive model, and finally, the optimization control of the system is achieved. This method enhances the robustness of standard model predictive control through both active and passive compensation, ensuring that the predefined constraints are still satisfied after disturbance compensation. Simulation results demonstrate that under external disturbances, the proposed method effectively compensates for the disturbances in the overhead crane system while ensuring that control constraints are satisfied at all times. Additionally, it addresses actuator saturation issues, thereby guaranteeing the system's operational performance.