Designing Uniaxial Magnetorheological Damper-based Prosthetic Knee and CT+PD Trajectory Tracking Control
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摘要: 针对传统假肢膝关节存在阻尼无法连续可调、仿生性不佳及价格高昂等问题，提出一种以磁流变阻尼器(Magnetorheological damper, MRD)为控制器件的新型磁流变假肢膝关节(Magnetorheological damper-based prosthetic knee, MRPK)。基于健康人在平地行走的步态数据，对单轴式MRPK进行结构设计，并建立其处于摆动相内的动力学模型，得到MRD的阻尼力需大于208.6 N及行程需大于33.3 mm。对MRD进行结构设计并利用ANSYS对其进行电磁场仿真分析，同时建立MRD的正向、逆向力学模型并得到其性能曲线。采用联合仿真的方法建立磁流变假肢膝关节控制系统，设计CT+PD轨迹跟踪控制器并与PD控制器对比，仿真得到CT+PD控制器的最大误差为-4.6°，而PD控制器的最大误差为12.3°。初步证明了CT+PD轨迹跟踪控制对MRPK摆动控制的有效性。Abstract: To solve the problems of traditional prosthetic knees such as nonadjustable damping, low imitation and high price, a magnetorheological damper-based prosthetic knee (MRPK) using magnetorheological damper (MRD) as control device is designed. Based on the gait data of healthy people walking on the ground, the structural design of the uniaxial MRPK was carried out, and its dynamic model in the swing phase was established. The damping force required by MRD is greater than 208.6 N and the stroke is greater than 33.3 mm. The structure of the MRD was designed and the simulation of electromagnetic field of the designed MRD was performed with the ANSYS. At the same time, the forward and reverse mechanical models of the MRD were established and its performance curves were obtained. The control system of the designed MRPK was established with the co-simulation method, and the computing torque plus PD (CT+PD) trajectory tracking controller was designed and compared with the PD controller. The results show that the maximum error of the CT+PD controller is -4.6°, while that of the PD controller is 12.3°, therefore proving that the CT+PD trajectory tracking control is effective for the swing control of the designed MRPK.
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Key words:
- prosthetic knee /
- magnetorheological damper /
- structural design /
- CT+PD control
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表 1 大腿及小腿摆动角度拟合参数
i a1i a2i a3i b1i b2i b3i 1 9.169 23.88 0.582 2.798 0.495 -2.289 2 9.522 14.17 0.041 12.5 1.494 2.525 3 23.54 37.13 3.735 5.175 2.398 1.184 4 10.37 3.573 9.817 19.38 -6.663 -2.905 5 -13.07 3.119 5.362 24.8 0.200 2 -2.367 6 1.833 1.89 19.13 27.25 -6.367 -0.363 
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表 2 磁流变假肢关键参数
参数名称 数值 大腿质量m1 1 kg 小腿质量m2 2.4 kg 大腿长度l1 460 mm 小腿长度l2 430 mm 大腿质心到髋关节长度lp1 360 mm 小腿质心到膝关节长度lp2 165 mm
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表 3 MRD关键参数
参数名称 数值 缸体内径D 30 mm 活塞头直径d1 28 mm 活塞杆直径d2 18 mm 有效阻尼长度L 10 mm 黏度η 0.8 Pa·s 匝数N 100
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[1] LARA-BARRIOS C M, BLANCO-ORTEGA A, GUZMÁN-VALDIVIA C H, et al. Literature review and current trends on transfemoral powered prosthetics[J]. Advanced Robotics, 2018, 32(2): 51-62 doi: 10.1080/01691864.2017.1402704 [2] OBA T, KADONE H, HASSAN M, et al. Robotic ankle-foot orthosis with a variable viscosity link using MR fluid[J]. IEEE/ASME Transactions on Mechatronics, 2019, 24(2): 495-504 doi: 10.1109/TMECH.2019.2894406 [3] MOUSAVI S H, SAYYAADI H. Optimization and testing of a new prototype hybrid MR brake with arc form surface as a prosthetic knee[J]. IEEE/ASME Transactions on Mechatronics, 2018, 23(3): 1204-1214 doi: 10.1109/TMECH.2018.2820065 [4] 胡国良, 刘丰硕, 刘浩. 位移差动自感式磁流变阻尼器设计与试验[J]. 农业机械学报, 2017, 48(11): 383-389, 397 doi: 10.6041/j.issn.1000-1298.2017.11.047HU G L, LIU F S, LIU H. Design and experiment of novel dispalcement differential self-induced magnetorheological damper[J]. Transactions of the Chinese Society for Agricultural Machinery, 2017, 48(11): 383-389, 397 (in Chinese) doi: 10.6041/j.issn.1000-1298.2017.11.047 [5] ANDRADE R M, FILHO A B, VIMIEIRO C B s, et al. Optimal design and torque control of an active magnetorheological prosthetic knee[J]. Smart Materials and Structures, 2018, 27(10): 105031 doi: 10.1088/1361-665X/aadd5c [6] PARK J, YOON G H, KANG J W, et al. Design and control of a prosthetic leg for above-knee amputees operated in semi-active and active modes[J]. Smart Materials and Structures, 2016, 25(8): 085009 doi: 10.1088/0964-1726/25/8/085009 [7] THIELE J, WESTEBBE B, BELLMANN M, et al. Designs and performance of microprocessor-controlled knee joints[J]. Biomedical Engineering, 2014, 59(1): 65-77 doi: 10.1515/bmt-2013-0069 [8] XIE H L, LIANG Z Z, LI F, et al. The knee joint design and control of above-knee intelligent bionic leg based on magneto-rheological damper[J]. International Journal of Automation and Computing, 2010, 7(3): 277-282 doi: 10.1007/s11633-010-0503-y [9] XU L, WANG D H, FU Q, et al. A novel four-bar linkage prosthetic knee based on magnetorheological effect: principle, structure, simulation and control[J]. Smart Materials and Structures, 2016, 25(11): 115007 doi: 10.1088/0964-1726/25/11/115007 [10] XU L, WANG D H, FU Q, et al. A novel motion platform system for testing prosthetic knees[J]. Measurement, 2019, 146: 139-151 doi: 10.1016/j.measurement.2019.04.073 [11] BERNAL-TORRES M G, MEDELLÍN-CASTILLO H I, ARELLANO-GONZÁLEZ J C. Design and control of a new biomimetic transfemoral knee prosthesis using an echo-control scheme[J]. Journal of Healthcare Engineering, 2018, 2018: 8783642 http://europepmc.org/articles/PMC5952505/ [12] 赵晓东, 刘作军, 苟斌, 等. 下肢假肢斜坡路况运动控制策略分析[J]. 决策与控制, 2019, 34(6): 1160-1168 https://www.cnki.com.cn/Article/CJFDTOTAL-KZYC201906005.htmZHAO X D, LIU Z J, GOU B, et al. Analysis of slope motion control strategy of lower limb prostheses[J]. Control and Decision, 2019, 34(6): 1160-1168 (in Chinese) https://www.cnki.com.cn/Article/CJFDTOTAL-KZYC201906005.htm [13] NANDI G C, IJSPEERT A J, CHAKRABORTY P, et al. Development of adaptive modular active leg (AMAL) using bipedal robotics technology[J]. Robotics and Autonomous Systems, 2009, 57(6-7): 603-616 doi: 10.1016/j.robot.2009.02.002 [14] FU Q, WANG D H, XU L, et al. A magnetorheological damper-based prosthetic knee (MRPK) and sliding mode tracking control method for an MRPK-based lower limb prosthesis[J]. Smart Materials and Structures, 2017, 26(4): 045030 doi: 10.1088/1361-665X/aa61f1 [15] ARNEZ-PANIAGUA V, RIFAÏ H, AMIRAT Y. Adaptive control of an actuated ankle foot orthosis for paretic patients[J]. Control Engineering Practice, 2019, 90: 207-220 doi: 10.1016/j.conengprac.2019.06.003 [16] EKKACHAI K, NILKHAMHANG I. Swing phase control of semi-active prosthetic knee using neural network predictive control with particle swarm optimization[J]. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2016, 24(11): 1169-1178 doi: 10.1109/TNSRE.2016.2521686 -
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