Dynamic Modeling and Adaptive Fuzzy Control of Spatial Deformation Pneumatic Leg Actuators With Error Constraints

ABSTRACT With the development of soft crawling robots, pneumatic soft actuators (PSAs) with complicated nonplanar structures are increasingly designed due to the capabilities of achieving compound robot movements. However, the current deformation accuracy of complex PSAs is insufficient to satisfy application requirements. Specifically, the dynamic properties of complex PSAs are still ambiguous and PSA deformation control methods remain lacking, which are caused by inherent characteristics, such as strong nonlinearity and hysteresis. To this end, based on self‐fabricated spatial deformation pneumatic leg actuators (SDPLAs), an equivalent dynamic model derived from Euler–Lagrange equations and a modified hysteresis model are established to form the new complete model of SDPLA systems, which accurately describes the bending deformation and hysteresis of SDPLAs at the same time. Furthermore, a novel model‐based adaptive fuzzy tracking controller is designed for SDPLAs, which addresses model uncertainties and unknown external torque, and achieves the accurate bending of each SDPLA part. Subsequently, the closed‐loop stability is rigorously proven by the Lyapunov theory. Finally, a series of experiments validates the effectiveness of the established dynamic and hysteresis models, the tracking control performance on time‐varying trajectories with different amplitudes, frequencies, and shapes, and the control robustness against disturbances.

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Publication Details

Journal
Journal of Field Robotics
Published
2025-09-01
DOI
https://doi.org/10.1002/rob.70055
Citations
1
Primary Topic
Soft Robotics and Applications
Type
article
Field-Weighted Citation Impact
0.67
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article

Dynamic Modeling and Adaptive Fuzzy Control of Spatial Deformation Pneumatic Leg Actuators With Error Constraints

Zhuoqing Liu, Qingxiang Wu, Zehao Qiu, Ning Sun et al.
1 citations
Journal of Field Robotics
Soft Robotics and Applications
0.67
article

Dynamic Modeling and Adaptive Fuzzy Control of Spatial Deformation Pneumatic Leg Actuators With Error Constraints

Zhuoqing Liu, Qingxiang Wu, Zehao Qiu, Ning Sun, Yongchun Fang
article en
1 citations

Abstract

ABSTRACT With the development of soft crawling robots, pneumatic soft actuators (PSAs) with complicated nonplanar structures are increasingly designed due to the capabilities of achieving compound robot movements. However, the current deformation accuracy of complex PSAs is insufficient to satisfy application requirements. Specifically, the dynamic properties of complex PSAs are still ambiguous and PSA deformation control methods remain lacking, which are caused by inherent characteristics, such as strong nonlinearity and hysteresis. To this end, based on self‐fabricated spatial deformation pneumatic leg actuators (SDPLAs), an equivalent dynamic model derived from Euler–Lagrange equations and a modified hysteresis model are established to form the new complete model of SDPLA systems, which accurately describes the bending deformation and hysteresis of SDPLAs at the same time. Furthermore, a novel model‐based adaptive fuzzy tracking controller is designed for SDPLAs, which addresses model uncertainties and unknown external torque, and achieves the accurate bending of each SDPLA part. Subsequently, the closed‐loop stability is rigorously proven by the Lyapunov theory. Finally, a series of experiments validates the effectiveness of the established dynamic and hysteresis models, the tracking control performance on time‐varying trajectories with different amplitudes, frequencies, and shapes, and the control robustness against disturbances.

Journal of Field RoboticsVol. 43(2)
Shenzhen Institute of Information Technology (CN), Nankai University (CN)
Openalex Percentile: Top 27%
Soft Robotics and Applications
0.67
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Dynamic Modeling and Adaptive Fuzzy Control of Spatial Deformation Pneumatic Leg Actuators With Error Constraints — Zhuoqing Liu, Qingxiang Wu, et al. · Journal of Field Robotics (2025) | TGRS Research Map | TGRS