Research on the Design and Control Method of Robotic Flexible Magneto-Rheological Actuator

To meet the safety and compliance requirements pertaining to robots when interacting physically with humans or the environment in unstructured settings such as households and factories, in this study, we focus on methods for the design and control of a flexible robotic magneto-rheological actuator (MRA). Firstly, for the magneto-rheological fluid clutch (MRC), which is the core component of the MRA, an equivalent magnetic circuit model was established to accurately calculate the magnetic field inside the clutch, and a thermal circuit model was constructed to analytically determine the operating temperature of each component. Considering practical engineering constraints, including mechanical structure, magnetic saturation, maximum current, and maximum temperature, a genetic algorithm was used to optimize parameters of the MRC. Secondly, based on the dynamic characteristics of the MRA, a dynamic model incorporating the motor, reducer, MRC, and load link was established. Given scenarios where torque sensors cannot be installed due to cost and structural space limitations, a model reference PID feedforward control strategy was designed. Torque was estimated using input current. Finally, an experimental platform was built, and static and dynamic torque output experiments were conducted. These experiments verified the excellent torque tracking performance of the designed MRA. Through multi-physics modeling, parameter optimization, and control strategy design, this paper provides a solution for flexible robotic joints that integrates high torque, high compliance, and safety.

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Publication Details

Journal
Sensors
Published
2025-11-12
DOI
https://doi.org/10.3390/s25226921
Primary Topic
Vibration Control and Rheological Fluids
Type
article
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0.00
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article

Research on the Design and Control Method of Robotic Flexible Magneto-Rheological Actuator

Guangzeng Chen, Yao Pengpeng, Sheng Jian, Ran Shi
Sensors
Vibration Control and Rheological Fluids
article

Research on the Design and Control Method of Robotic Flexible Magneto-Rheological Actuator

Guangzeng Chen, Yao Pengpeng, Sheng Jian, Ran Shi
article en

Abstract

To meet the safety and compliance requirements pertaining to robots when interacting physically with humans or the environment in unstructured settings such as households and factories, in this study, we focus on methods for the design and control of a flexible robotic magneto-rheological actuator (MRA). Firstly, for the magneto-rheological fluid clutch (MRC), which is the core component of the MRA, an equivalent magnetic circuit model was established to accurately calculate the magnetic field inside the clutch, and a thermal circuit model was constructed to analytically determine the operating temperature of each component. Considering practical engineering constraints, including mechanical structure, magnetic saturation, maximum current, and maximum temperature, a genetic algorithm was used to optimize parameters of the MRC. Secondly, based on the dynamic characteristics of the MRA, a dynamic model incorporating the motor, reducer, MRC, and load link was established. Given scenarios where torque sensors cannot be installed due to cost and structural space limitations, a model reference PID feedforward control strategy was designed. Torque was estimated using input current. Finally, an experimental platform was built, and static and dynamic torque output experiments were conducted. These experiments verified the excellent torque tracking performance of the designed MRA. Through multi-physics modeling, parameter optimization, and control strategy design, this paper provides a solution for flexible robotic joints that integrates high torque, high compliance, and safety.

SensorsVol. 25(22)
Shenzhen Polytechnic University (CN), Harbin Institute of Technology (CN)
Openalex Percentile: Top 64%
Vibration Control and Rheological Fluids
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Research on the Design and Control Method of Robotic Flexible Magneto-Rheological Actuator — Guangzeng Chen, Yao Pengpeng, et al. · Sensors (2025) | TGRS Research Map | TGRS