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<p>The short-stroke linear motors are susceptible to external cyclic and acyclic disturbances during high-precision repetitive positioning. In the current work, a high-precision repetitive positioning control strategy based on generalized adaptive super-twisting sliding mode control (GAST-SMC) and iterative learning control (ILC) is innovatively proposed, building upon the “feedforward + feedback” framework. On the one hand, the feedback controller integrates the position loop’s GAST-SMC and the current loop’s deadbeat predictive control (DPC) algorithm. The GAST-SMC offers faster convergence speed and higher adjustability than the traditional adaptive super-twisting mode control, and the DPC algorithm in the current loop offers higher control precision than the traditional PI control, collectively contributing to enhancing control precision and robustness. On the other hand, the feedforward controller integrates the ILC for repetitive positioning tasks and the disturbance observers for position and current loops. The ILC is used to overcome the periodic disturbances during motor operation. The sliding mode load observer is used to observe the disturbances in the position loop and compensate for them in the GAST-SMC. The sliding mode parameter perturbance observer is used to observe the perturbations of the current loop and compensate for them in the DPC. Finally, the excellent control performance of the proposed control strategy is verified by physical experiments.</p>

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High-precision repetitive positioning of short-stroke linear motors based on generalized adaptive super-twisting sliding mode and iterative learning

  • 期刊论文

  • 发表日期：

    2025年6月26日

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  • Chenyan Sun,
  • Yifan Zou,
  • Yihang Liu

摘要

The short-stroke linear motors are susceptible to external cyclic and acyclic disturbances during high-precision repetitive positioning. In the current work, a high-precision repetitive positioning control strategy based on generalized adaptive super-twisting sliding mode control (GAST-SMC) and iterative learning control (ILC) is innovatively proposed, building upon the “feedforward + feedback” framework. On the one hand, the feedback controller integrates the position loop’s GAST-SMC and the current loop’s deadbeat predictive control (DPC) algorithm. The GAST-SMC offers faster convergence speed and higher adjustability than the traditional adaptive super-twisting mode control, and the DPC algorithm in the current loop offers higher control precision than the traditional PI control, collectively contributing to enhancing control precision and robustness. On the other hand, the feedforward controller integrates the ILC for repetitive positioning tasks and the disturbance observers for position and current loops. The ILC is used to overcome the periodic disturbances during motor operation. The sliding mode load observer is used to observe the disturbances in the position loop and compensate for them in the GAST-SMC. The sliding mode parameter perturbance observer is used to observe the perturbations of the current loop and compensate for them in the DPC. Finally, the excellent control performance of the proposed control strategy is verified by physical experiments.