Improved decoupling for maglev planar actuators with coil-to-coil misalignments: A LM iterative commutation tuning algorithm.

Authors

Guangyi Qin, Shuo Song, Li Li, Yang Liu, Limin Zou, Jiubin Tan

Published in

ISA transactions. Oct 26, 2026. Epub Oct 26, 2026.

Abstract

The maglev planar actuator is a core component of ultra-precision motion stages in various industrial applications. Commutation serves as the critical first step in decoupling; however, its performance is usually limited by the mismatch between the actual and theoretical electromagnetic models. To address this issue, this paper proposes a data-based Levenberg-Marquardt (LM) iterative commutation tuning strategy. Unlike existing methods that consider only mover-to-stator misalignments, the proposed strategy models and tunes the phase errors of individual coils, thereby providing a more accurate commutation model. Moreover, the LM algorithm is employed to solve the resulting nonlinear least-squares problem, providing improved robustness and tuning performance compared with the gradient-descent (GD) algorithm. Experimental results on a moving-coil maglev planar actuator (MCMPA) show that the proposed strategy remains effective with tuning points selected along the X DOF, along the Y DOF, or distributed along both DOFs, and reduces the peak Z-DOF coupling error induced by X/Y-DOF movements by at least 47.7% under high-dynamic tracking. Furthermore, the proposed strategy outperforms the GD-based tuning method and the approach considering only mover-to-stator misalignments, while the tuned parameters can also be successfully applied to the direct decoupling model.

PMID:
42957490
Bibliographic data and abstract were imported from PubMed on 30 Oct 2026.

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