Design, Modeling and Control of Bionic Knee in Artificial Leg

  • Hualong Xie Department of Mechanical Engineering and Automation, Northeastern University
  • Yao Xie
  • Fei Li

Abstract

The biped robot with heterogeneous legs (BRHL) greatly facilitates the development of intelligent lower-limb prosthesis (ILLP). In the BRHL, the remaining leg of the amputee is simulated by an artificial leg, which provides the bionic leg with the precise gait following trajectory. Therefore, the artificial leg must closely mimic the features of the human leg. After analyzing the motion mechanism of the human knee, this paper designs a four-link bionic knee in light of the coexistence of rolling and sliding between the femur, the meniscus and the tibia. Drawing on the driving mechanism of leg muscles, two pneumatic artificial muscles (PAMs) were adopted to serve as the extensor and flexor muscles on the thigh. The two PAMs move in opposite direction, driving the knee motions in the artificial leg. To overcome the complexity of traditional PAM modelling methods, the author set up a PAM feature test platform to disclose the features of the PAMs, and built static and dynamic nonlinear mathematical models of the PAMs based on the test data. Next, a proportional-integral-derivative (PID) closed loop controller and sliding mode controller was designed for the bionic knee, referring to the kinetics equation of the knee. Through experimental simulation, it is confirmed that the proposed controller can accurately control the position of the four-link bionic knee, and that the designed bionic knee and PAM driving mode are both correct.

References

[1] Chen, D.H.; Ushijima, K. (2013); Prediction of the mechanical performance of mcKibben artificial muscle actuator, International Journal of Mechanical Science, 78(1), 183-192, 2013.
https://doi.org/10.1016/j.ijmecsci.2013.11.010

[2] Chou, C.P.; Hannaford, B. (1996); Measurement and modeling of mcKibben pneumatic artificial muscles, IEEE Transactions on Robotics and Automation, 12(1), 90-102, 1996.
https://doi.org/10.1109/70.481753

[3] Ganguly, S.; Garg, A.; Pasricha, A.; Dwivedy, S.K. (2012); Control of pneumatic artificial muscle system through experimental modelingm, Mechatronics, 22(8), 1135-1147, 2012.
https://doi.org/10.1016/j.mechatronics.2012.09.010

[4] Gong, S.Y.; Yang, P.; Song, L.; Chen, L.L. (2011); Simulation of swing phase dynamics in trans-femoral prostheses based on MATLAB, Journal of Hebei University of Technology, 40(2), 6-9, 2011.

[5] Jouppila, V.; Gadsden, S.A.; Ellman, A. (2014); Experimental comparisons of sliding mode controlled pneumatic muscle and cylinder actuators, Journal of Dynamic Systems Measurement&Control, 136(4), 543-552, 2014.
https://doi.org/10.1115/1.4026873

[6] Pandit, S.; Godiyal, A.K.; Vimal, A.K.; Singh, U.; Joshi, D.; Kalyanasundaram, D. (2018); An affordable insole-sensor-based trans-femoral prosthesis for normal gait, Sensors, 18(3), 2018.
https://doi.org/10.3390/s18030706

[7] Pillai, M.V.; Kazerooni, H.; Hurwich, A. (2001); Design of a semi-active knee-ankle Prosthesis, Proceedings of IEEE International Conference on Robotics and Automation,IEEE, Shanghai, China, 5293-5300, 2001.

[8] Radcliffe, C.W. (2003); Biomechanics of knee stability control with four-bar prosthetic knees, ISPO Australia Annual Meeting, 2003.

[9] Sanville, F.E. (1971); Van Brussel, H. (1971); New method of specifying the flow capacity of pneumatic fluid power valves, Hydraulic Pneumatic, 17(195), 120-126, 1971.

[10] Su, B.Y.; Wang, J.; Liu, S.Q.; Sheng, M.; Jiang, J.; Xiang,K. (2019); A CNN-Based Method for Intent Recognition Using Inertial Measurement Units and Intelligent Lower Limb Prosthesis, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 27(5), 1032- 1042, 2019.
https://doi.org/10.1109/TNSRE.2019.2909585

[11] Tian, H.; Ma, L.; Zhu, X.; Dang, X. (2019); Grinding method, trajectory planning and simulation of a 3 DOF knee grinding robot, International Journal of Simulation Modelling, 18(1), 150-162, 2019.
https://doi.org/10.2507/IJSIMM18(1)CO2

[12] Vo-Minh, T.; Tjahjowidodo, T.; Ramon, H.; Van Brussel, H. (2011); A new approach to modeling hysteresis in a pneumatic artificial muscle using the maxwell-slip model, IEEE/ASME Transactions on Mechatronics, 16(1), 177-186, 2011.
https://doi.org/10.1109/TMECH.2009.2038373

[13] Vo-Minh, T.; Tjahjowidodo, T.; Ramon, H.; Van Brussel, H. (2010); Cascade position control of a single pneumatic artificial muscle-mass system with hysteresis compensation, Mechatronic, 20(3), 402-414, 2010.
https://doi.org/10.1016/j.mechatronics.2010.03.001

[14] Wang, S.F., Sato, K.; Kagawa, T. (2014); Precise positioning of pneumatic artificial muscle systems, Journal of Flow Control, Measurement&Visualization, 2(4), 138-153, 2014.
https://doi.org/10.4236/jfcmv.2014.24016

[15] Xie, H.L.; Chen, K.L.; Li, F. (2015) ; Bionic artificial leg design and control simulation based on fuzzy PID control algorithm, Proceedings of IEEE International Conference on Cyber Technology in Automation, Control and Intelligent Systems, IEEE, Shenyang, China, 2097-2102, 2015.
https://doi.org/10.1109/CYBER.2015.7288272

[16] Xie, H.L.; He, N.; Li, F.; ieYang, J.Y. (2015); The bionic design and system identification of intelligent bionic leg with magneto-rheological damper, Tehnicki Vjesnik,, 22(5), 1093-1098, 2015.
https://doi.org/10.17559/TV-20150731100315

[17] Xie, H.L.; Liang, Z.Z.; Li, F.; Guo, L.X. (2010); The Knee Joint Design and Control of above Knee Intelligent Bionic Leg Based on Magneto-rheological Damper, International Journal of Automation and Computing, 7(3), 277-282, 2010.
https://doi.org/10.1007/s11633-010-0503-y

[18] Xie, H.L.; Liu, Z.B.; Yang, J.Y. (2016); Modelling of Magnetorheological Damper for Intelligent Bionic Leg and Simulation of Knee Joint Movement Control, International Journal of Simulation Modelling, 15(1), 144-156, 2016
https://doi.org/10.2507/IJSIMM15(1)CO2

[19] Young, A.; Hargrove, L. (2016); A classification method for userindependent intent recognition for transfemoral amputees using powered lower limb prostheses, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(2), 217-225, 2016.
https://doi.org/10.1109/TNSRE.2015.2412461

[20] Zhang, X.F.; Fu, H.Q.; Wang, X.T.; Li, G.L.; Yang, R.; Liu, Y. (2016); Design of a novel bionic prosthetic knee joint, Assembly Automation, 36(4), 398-404, 2016.
https://doi.org/10.1108/AA-08-2015-066

[21] Zhang, Z.H.; Hu, C. (2015); Multi-model stability control method of underactuated biped robots based on imbalance degrees, International Journal of Simulation Modelling,14(4), 647-657, 2015.
https://doi.org/10.2507/IJSIMM14(4)7.318

[22] Zhu, J.M.; Huang, C.Y.; Lei, J.T.; Qi, B.C. (2017); Position/Stiffness Control of Antagonistic Bionic Joint Driven by Pneumatic Muscles Actuators, Journal of Mechanical Engineering, 53(13), 64-74, 2017.
https://doi.org/10.3901/JME.2017.13.064
Published
2019-11-17
How to Cite
XIE, Hualong; XIE, Yao; LI, Fei. Design, Modeling and Control of Bionic Knee in Artificial Leg. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 14, n. 5, p. 733-752, nov. 2019. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/3622>. Date accessed: 02 july 2020. doi: https://doi.org/10.15837/ijccc.2019.5.3622.

Keywords

Bionic knee, biped robot with heterogeneous legs (BRHL), pneumatic artificial muscle (PAM), high-speed on-off valve, proportional-integral-derivative (PID) control