Adaptive Feedforward Control Based on Recursive Least Squares Algorithm for the Biaxial Maglev Planar-Motor-Driven Gantry System

The biaxial maglev planar- motor-driven gantry system is used to achieve high-speed and high-precision trajectory tracking of both the x-axis and y-axis simultaneously. However, due to the significant model uncertainty of the system, traditional acceleration feedforward based on ideal mass cannot achieve precise compensation for position errors. This article proposes an adaptive feedforward control method, which combines the experimental measurement results of position controller output and acceleration signal, and uses recursive least squares (RLS) algorithm to update controller parameters. It has the characteristics of simple implementation method and small computational complexity. Both simulation and experimental results have shown that this method can effectively suppress repeatable periodic disturbances introduced by the reference during acceleration and deceleration phases, improving adaptability and performance for different tasks.