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This research advances haptic feedback technology by introducing a magnetically self-sealed magnetorheological fluid actuator with high-fidelity torque control, directly addressing the need for safe and perceptive human-robot interaction. The study demonstrates significant improvements in stability and repeatability through advanced PWM excitation and nonlinear modeling, offering a practical solution for next-generation robotic collaboration systems.
Magnetically Self-Sealed MR Haptic Actuator With PWM-Based Excitation and High-Fidelity Torque Control
arXiv:2608.19635v1 Announce Type: new Abstract: Accurate and stable torque rendering is essential for safe and perceptive human--machine interaction. Magnetorheological fluid (MRF)-based actuators offer a compact and rapidly controllable solution for haptic feedback, but their practical implementation requires reliable fluid sealing, low-hysteresis excitation, accurate torque control, and stable long-duration operation. This article presents an integrated MRF haptic system featuring a compact magnetically self-sealed rotary actuator, low-hysteresis PWM operation, high-fidelity model-based torque rendering, and stable performance during long-time operation. Magnetostatic simulation guides the arrangement of magnetic and nonmagnetic materials to focus flux in the multidisk torque and permanent-magnet sealing regions, enabling a maximum 600 N$\cdot$mm/A output. Experiments show that higher PWM frequencies reduce hysteresis and improve repeatability. At 10 kHz, the response is represented by a nonlinear model that varies with the direction and speed of torque change. The real-time controller combines feedforward, hysteresis compensation, PI feedback, and sliding-mode correction. Compared with PID, it reduces square-wave overshoot, undershoot, and steady-state RMSE by 77.4\%, 61.9\%, and 68.3\%, respectively. It tracks sinusoidal and biomechanics-model-based references, and a 1.5-h test shows only a 2.5 $^\circ$C rise near the coil with no clear tracking loss. This high-fidelity torque rendering will fundamentally transform human--robot collaboration by making interactions safer, more efficient, and more intuitive.
Abstract:Accurate and stable torque rendering is essential for safe and perceptive human--machine interaction. Magnetorheological fluid (MRF)-based actuators offer a compact and rapidly controllable solution for haptic feedback, but their practical implementation requires reliable fluid sealing, low-hysteresis excitation, accurate torque control, and stable long-duration operation. This article presents an integrated MRF haptic system featuring a compact magnetically self-sealed rotary actuator, low-hysteresis PWM operation, high-fidelity model-based torque rendering, and stable performance during long-time operation. Magnetostatic simulation guides the arrangement of magnetic and nonmagnetic materials to focus flux in the multidisk torque and permanent-magnet sealing regions, enabling a maximum 600 N$\cdot$mm/A output. Experiments show that higher PWM frequencies reduce hysteresis and improve repeatability. At 10 kHz, the response is represented by a nonlinear model that varies with the direction and speed of torque change. The real-time controller combines feedforward, hysteresis compensation, PI feedback, and sliding-mode correction. Compared with PID, it reduces square-wave overshoot, undershoot, and steady-state RMSE by 77.4\%, 61.9\%, and 68.3\%, respectively. It tracks sinusoidal and biomechanics-model-based references, and a 1.5-h test shows only a 2.5 $^\circ$C rise near the coil with no clear tracking loss. This high-fidelity torque rendering will fundamentally transform human--robot collaboration by making interactions safer, more efficient, and more intuitive.
Submitted to IEEE/ASME Transactions on Mechatronics. 16 pages, 9 figures, including supplementary material
Robotics (cs.RO); Systems and Control (eess.SY)
arXiv:2608.19635 [cs.RO]
(or arXiv:2608.19635v1 [cs.RO] for this version)
https://doi.org/10.48550/arXiv.2608.19635 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
Supplementary_Materials.pdf
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