Design and Control of a Pneumatic Artificial Muscle Actuated Exoskeleton Robot for Upper Limb Rehabilitation

doi:10.3901/JME.2025.03.225

Abstract

Abstract: A pneumatic artificial muscle (PAM) actuated exoskeleton is developed for upper limb rehabilitation and augmentation. Different from rigid actuation, the developed exoskeleton combines PAM and rigid link to achieve both flexible actuation and high-precision movement. This helps to reduce the risk of unwanted injury to users during the rehabilitation process. In structural design, a combination of direct driven and cable driven is adopted to provide 3 degrees-of-freedom actuation for the shoulder and elbow joints. The compact structure helps to facilitate its wearability. This research presents the kinematics modeling of the exoskeleton, and dynamic modeling is then finished using the three-element model of PAM and Lagrange method. For the hysteresis nonlinearity of PAM, the combination of direct inverse modeling and adaptive projection algorithm is adopted to achieve adaptive hysteresis compensation without offline modeling and inversion. Finally, the feasibility of the exoskeleton and the proposed controller is verified via hysteresis compensation and anti-interference experiments. Experimental results show that the developed exoskeleton features both flexible actuation and high motion accuracy, satisfying the needs of upper limb rehabilitation and augmentation.

Key words: pneumatic artificial muscle, upper limb exoskeleton, rehabilitation robot, hysteresis compensation

CLC Number:

TG156

QIN Yanding, FAN Jiade, ZHANG Haoqi, TIAN Mengqiang, HAN Jianda. Design and Control of a Pneumatic Artificial Muscle Actuated Exoskeleton Robot for Upper Limb Rehabilitation[J]. Journal of Mechanical Engineering, 2025, 61(3): 225-236.

Add to citation manager EndNote|Reference Manager|ProCite|BibTeX|RefWorks

URL: http://www.cjmenet.com.cn/EN/10.3901/JME.2025.03.225

http://www.cjmenet.com.cn/EN/Y2025/V61/I3/225

References

[1] MINAGAWA H，YAMAMOTO N，ABE H，et al. Prevalence of symptomatic and asymptomatic rotator cuff tears in the general population:From mass-screening in one village[J]. Journal of Orthopaedics，2013，10(1):8-12.
[2] TANG Z C，YANG H C，ZHANG L K，et al. Effect of shoulder angle variation on sEMG-based elbow joint angle estimation[J]. International Journal of Industrial Ergonomics，2018，68:280-289.
[3] 李响，周人龙，张洪蕊，等. 上肢机器人对肩袖损伤术后患者的疗效观察[J]. 中国康复，2022，37(7):410-413. LI Xiang，ZHOU Renlong，ZHANG Hongrui，et al. Efficacy of upper limb robot in patients after rotator cuff injury[J]. Chinese Journal of Rehabilitation，2022，37(7):410-413.
[4] FASOLI S E，KREBS H I，STEIN J，et al. Effects of robotic therapy on motor impairment and recovery in chronic stroke[J]. Archives of Physical Medicine and Rehabilitation，2003，84(4):477-482.
[5] XU B G，PENG S，SONG A G，et al. Robot-aided upper-limb rehabilitation based on motor imagery EEG[J]. International Journal of Advanced Robotic Systems，2011，8(4):88-97.
[6] PIRONDINI E，COSCIA M，MARCHESCHI S，et al. Evaluation of the effects of the arm light exoskeleton on movement execution and muscle activities:A pilot study on healthy subjects[J]. Journal of NeuroEngineering and Rehabilitation，2016，13:9.
[7] 申慧敏，葛瑞康，葛迪，等. 基于肩部协同运动特征的康复外骨骼设计与人机相容性分析[J]. 机械工程学报，2022，58(19):34-44. SHEN Huimin，GE Ruikang，GE Di，et al. Rehabilitation exoskeleton design and human-machine compatibility analysis based on shoulder co-movement characteristics[J]. Journal of Mechanical Engineering，2022，58(19):34-44.
[8] 程杨，潘尚峰. 一种多自由度康复外骨骼机械臂的虚拟分解控制[J]. 机械工程学报，2022，58(9):21-30. CHENG Yang，PAN Shangfeng. Virtual decomposition control of multi-degree-of-freedom rehabilitation exoskeleton robotic arm[J]. Journal of Mechanical Engineering，2022，58(9):21-30.
[9] 宋遒志，王晓光，王鑫，等. 多关节外骨骼助力机器人发展现状及关键技术分析[J]. 兵工学报，2016，37(1):172-185. SONG Qiuzhi，WANG Xiaoguang，WANG Xin，et al. Analysis of the development status and key technologies of multi-articular exoskeletons to assist robots[J]. Acta Armamentarii，2016，37(1):172-185.
[10] BOGUE R. Exoskeletons and robotic prosthetics:A review of recent developments[J]. Industrial Robot-an International Journal，2009，36(5):421-427.
[11] KLEIN J，SPENCER S，ALLINGTON J，et al. Optimization of a parallel shoulder mechanism to achieve a high-force，low-mass，robotic-arm exoskeleton[J]. IEEE Transactions on Robotics，2010，26(4):710-715.
[12] CHEN S，CHEN Z，YAO B，et al. Adaptive robust cascade force control of 1-DOF hydraulic exoskeleton for human performance augmentation[J]. IEEE/ASME Transactions on Mechatronics，2017，22(2):589-600.
[13] VO-MINH T，TJAHJOWIDODO T，RAMON H，et al. A new approach to modeling hysteresis in a pneumatic artificial muscle using the Maxwell-slip model[J]. IEEE/ASME Transactions on Mechatronics，2011，16(1):177-186.
[14] TANG Z，ZHANG K，SUN S，et al. An upper-limb power-assist exoskeleton using proportional myoelectric control[J]. Sensors (Basel)，2014，14(4):6677-6694.
[15] XING K X，XU Q，HE J P，et al. A wearable device for repetitive hand therapy[C]// 2nd IEEE RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics. Piscataway，USA:IEEE，2008:919-923.
[16] JIANG X Z，HUANG X H，XIONG C H，et al. Position control of a rehabilitation robotic joint based on neuron proportion-integral and feedforward control[J]. Journal of Computational and Nonlinear Dynamics，2012，7(2):024502.
[17] XIONG C H，JIANG X Z，SUN R L，et al. Control methods for exoskeleton rehabilitation robot driven with pneumatic muscles[J]. Industrial Robot-an International Journal，2009，36(3):210-220.
[18] MENG W，LIU Q，ZHANG M M，et al. Compliance adaptation of an intrinsically soft ankle rehabilitation robot driven by pneumatic muscles[C]// IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)，F，2017.
[19] HUSSAIN S，XIE S Q，JAMWAL P K. Robust nonlinear control of an intrinsically compliant robotic gait training orthosis[J]. IEEE Transactions on Systems Man Cybernetics- Systems，2013，43(3):655-665.
[20] 谢胜龙，刘海涛，梅江平. 气动人工肌肉迟滞-蠕变特性研究现状与进展[J]. 系统仿真学报，2018，30(3):809-823. XIE Shenglong，LIU Haitao，MEI Jiangping. Research status and progress of aerodynamic artificial muscle retardation-creep characteristics[J]. Journal of System Simulation，2018，30(3):809-823.
[21] REYNOLDS D B，REPPERGER D W，PHILLIPS C A，et al. Modeling the dynamic characteristics of pneumatic muscle[J]. Annals of Biomedical Engineering，2003，31(3):310-317.
[22] ZHANG D H，ZHAO X G，HAN J D. Active model-based control for pneumatic artificial muscle[J]. IEEE Transactions on Industrial Electronics，2017，64(2):1686-1695.
[23] QU S C，XIA X H，ZHANG J F. Dynamics of discrete-time sliding-mode-control uncertain systems with a disturbance compensator[J]. IEEE Transactions on Industrial Electronics，2014，61(7):3502-3510.
[24] ZOU J，YAN P N，DING N Y，et al. Feedback-cascaded inverse feedforward for viscoelastic creep，hysteresis and cross-coupling compensation in dielectric-elastomer actuated XY stages[C]//IEEE/ASME International Conference on Advanced Intelligent Mechatronics(AIM)， 2017.
[25] LI Z，SHAN J J，GABBERT U. A direct inverse model for hysteresis compensation[J]. IEEE Transactions on Industrial Electronics，2021，68(5):4173-4181.
[26] QIN Y D，TIAN Y L，ZHANG D W，et al. A novel direct inverse modeling approach for hysteresis compensation of piezoelectric actuator in feedforward applications[J]. IEEE/ASME Transactions on Mechatronics，2013，18(3):981-989.
[27] QIN Y D，DUAN H，HAN J D. Direct inverse hysteresis compensation of piezoelectric actuators using adaptive kalman filter[J]. IEEE Transactions on Industrial Electronics，2022，69(9):9385-9395.
[28] 秦岩丁，徐圆凯，韩建达. 气动人工肌肉驱动的肘关节辅助机器人迟滞补偿[J]. 机器人，2021，43(4):453-462. QIN Yanding，XU Yuankai，HAN Jianda. Pneumatic artificial muscle-driven elbow assist robot hysteresis compensation[J]. Robot，2021，43(4):453-462.
[29] QIN Y D，DUAN H. Single-neuron adaptive hysteresis compensation of piezoelectric actuator based on Hebb learning rules[J]. Micromachines (Basel)，2020， 11(1):84.