Model Prediction based Online Feedforward Compensation Control of Maglev Planar Motor with Comparative Investigation

Abstract

Maglev planar motor is a novel planar motion device in precision/ultra-precision industry, while its precision motion control still needs further study. In this paper, a model prediction based online feedforward compensation (MP-OFC) control strategy is proposed for maglev planar motor to achieve excellent tracking performance. A system prediction model considering external disturbances and unmodeled factors is established to accurately predict tracking errors at future sampling moments online. Consequently, an iterative calculation scheme is designed to generate the feedforward compensation term as reference trajectory modification during real-time motion. Comparative simulation experiments consistently validate that the proposed MP-OFC strategy outperforms other controllers much, and the MP-OFC achieves excellent tracking accuracy for various trajectories even under complicated external disturbances.