Preprints
https://doi.org/10.5194/ms-2026-193
https://doi.org/10.5194/ms-2026-193
29 Oct 2026
 | 29 Oct 2026
Status: this preprint is currently under review for the journal MS.

Hysteretic switching active disturbance rejection control for the servo drives of a skating-training cable robot

Heyu Shi, Baihang Wang, Xue Zhao, Tong Tong, and Dandan Han

Abstract. Whether a skating-training robot reproduces the prescribed motion depends on whether its servo layer can follow the motor-angle reference amplified by the screw transmission and the cable geometry. Switching active disturbance rejection control improves the large-error response by switching between linear and nonlinear corrections, but the switching frequency and the tracking accuracy lack a quantitative relation, and the hysteresis width is selected without a stated rule. This paper builds an integrated model from cable geometry and screw transmission to the permanent-magnet synchronous motor and gives the torque, speed and voltage margins of each drive; it then proposes a state-preserving hysteretic implementation in which two normalized switching variables act on the observer and feedback corrections separately, with a hysteresis band added. Six controller families are compared at fixed gains with equal tuning effort over 154 cases: the 30 rad step overshoot falls from 52.171% to 0.311%, the maximum error in the load interval falls from 0.101 rad to 0.0447 rad, and the number of mode actions falls from 46 to 18 at a hysteresis width of 0.2. With the switching frequency taken as a design variable, the servo layer can set the switching count to its target while preserving tracking quality, which offers a reusable parameterized method for the servo design of comparable cable robots.

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Heyu Shi, Baihang Wang, Xue Zhao, Tong Tong, and Dandan Han

Status: open (until 05 Dec 2026)

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Heyu Shi, Baihang Wang, Xue Zhao, Tong Tong, and Dandan Han
Heyu Shi, Baihang Wang, Xue Zhao, Tong Tong, and Dandan Han
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Latest update: 29 Oct 2026
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Short summary
Robots that train speed skaters guide the legs with cables driven by electric motors. Mode changes wear the drives, yet their frequency is rarely measured. We modelled the chain from leg motion to motor behaviour and built a controller that switches only when needed, keeping its disturbance estimate. Tests show joints no longer shoot past the target, load errors halve, and switching falls by sixty per cent without losing tracking. Switching frequency can thus be designed, not merely accepted.
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