Academic Journal of Engineering and Technology Science, 2024, 7(4); doi: 10.25236/AJETS.2024.070409.
Rui Gong1, Ruiyao Li2, Siyi Zuo3
1School of Mechanical and Electronic Engineering, Wuhan University of Technology, Wuhan, China
2School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan, China
3School of Management, Wuhan University of Technology, Wuhan, China
To support the research of walking assistance and rehabilitation equipment for elderly stroke patients, a lower limb rehabilitation exoskeleton robot structure is designed to address the degree of freedom and joint layout difficulties in current serial humanoid lower limb rehabilitation exoskeletons. A simulation model was built using Matlab/Simulink and auxiliary plugins, with corresponding PID and fuzzy PID controllers designed and dynamic tuning of PID parameters carried out. To evaluate the controller’s anti-interference performance more accurately, a method for simulating patient spasticity as an evaluation experiment was proposed. The performance of the controller under two different assessment methods was compared and analyzed, showing that assessing through simulated patient spasticity can better stimulate the adaptive ability of the controller, which analyzes its protective effect on patients and helps optimize the control algorithm design and performance evaluation of lower limb rehabilitation exoskeletons.
stroke; movement rehabilitation; lower limb rehabilitation exoskeleton robot; fuzzy PID control; Simulink; control system simulation; performance evaluation
Rui Gong, Ruiyao Li, Siyi Zuo. Design and Control of Lower Limb Rehabilitation Exoskeleton Based on Simulink. Academic Journal of Engineering and Technology Science (2024) Vol. 7, Issue 4: 53-64. https://doi.org/10.25236/AJETS.2024.070409.
[1] Wu L , Zhao R , Li Y , et al. Optimal Design of Adaptive Robust Control for the Delta Robot with Uncertainty: Fuzzy Set-Based Approach[J]. Applied Sciences, 2020, 10(10):3472. DOI:10.3390/app10103472.
[2] Deaconescu T, Deaconescu A. Pneumaticmuscle actuated isokinetic equipment for there habilitation of patients with disabilities of the bearing joints [C]// International Multi-Conference of Engineersand Computer Scientists, Hongkong, 2009, 2:1823-1827.
[3] Yano H, Kasai K.Sharing sense of walking with locomotion interfaces [J].International Journal of Human Computer Interaction, 2005, 17(4):447-462.
[4] NADITZ A. Medical connectivity-new frontiers: Telehealth innovations of 2010 [J].Telemedicine ande-Health, 2010, 6(10):986- 992.
[5] Zeilig G, Weingarden H, Zwecker M, et al. Safety and tolerance of the ReWalk™ exoskeleton suit for ambulation by people with complete spinal cord injury: A pilot study[J]. The Journal of Spinal Cord Medicine, 2012, 35(2): 96-101.
[6] Ikeuchi Y, Ashihara J, Hiki Y, et al. Walking Assist Device with BodyweightSupport System[C/OL] // IEEE/RSJ International Conference on Intelligent Robotsand Systems. St. Louis : IEEE, 2009 : 4073-4079. http://dx.doi.org/10.1109/IROS.2009.5354543.
[7] Yunjie Miao. Research on mechanism performance design method of new lower limb exoskeleton[D]. Shanghai Jiao Tong University, 2017.
[8] Han J , Wang P , Dong F ,et al.Optimal design of adaptive robust control for a planar two-DOF redundantly actuated parallel robot[J].Nonlinear dynamics, 2021(3):105.
[9] Hongyue Hu, Likun Hu, Yida Liu, Et Al. Control method for the soft lower limb exosuit[J]. Chinese Journal of Scientific Instrument, 2020, 41(03):184-191.DOI:10.19650/j.cnki.cjsi.J1905946.
[10] Zhang Zheng, Zhao Liping, Liang Yiwei. Research of Control Method for Lower Limb Exoskeleton Trajectory Tracking Based on Differential Gear Train [J]. Coal Technology, 2015, 34(04): 305-307.DOI:10.13301/j.cnki.ct.2015.04.119.
[11] Dong F , Han J , Chen Y H ,et al. A Novel Robust Constraint Force Servo Control for Under‐actuated Manipulator Systems: Fuzzy and Optimal[J]. Asian Journal of Control, 2017. DOI:10.1002/asjc.1677.
[12] Gao Moyao. Research on structural design and gait planning method of lower limb exoskeleton rehabilitation robot[D]. Changchun University of Technology, 2022. DOI: 10.27805/d.cnki.gccgy.2022. 000900.
[13] Zhou Haitao. Research On Mechanism Designand Control Strategy Of The Lower Extremity Rehabilitation Exoskeleton [D].Harbin Institute of Technology, 2016.
[14] Chen Hui. Lower Limb Power Exoskeletoncreature - Mechanical System Simulation And Design Of Drive Unit [D]. Harbin Institute of Technology, 2014.
[15] Zhang Zongwei. Research on the Exoskeleton For Walking Assistance To The Physically Weak Persons Physically Weak Persons [D]. Harbin Institute of Technology, 2022. DOI:10.27061/d. cnki.ghgdu.2021.000338.
[16] Zhang Yan, Li Fanru, Li Wei, Liu Zuojun. Dynamic Analysis and Simulation of the Lower Extremity Exoskeleton Based on Human-Machine Interaction [J]. Applied Mathematics and Mechanics, 2019, 40(7):780-790.
[17] National Bureau of Technical Supervision. Chinese adult body size: GB/T 10000-1988[S]. 1988.
[18] Shen Yongkang. Design and Fuzzy PID Control of Lower Limb Rehabilitation Exoskeleton Robot [D]. Jianghan University, 2023.DOI:10.27800/d.cnki.gjhdx.2023.000176.
[19] National Bureau of Technical Supervision. Adult Human Inertia Parameters: GB/T 17245-2004.
[20] El-Sousy F F M , Amin M M , Mohammed O A .Robust Optimal Control of High-Speed Permanent-Magnet Synchronous Motor Drives via Self-Constructing Fuzzy Wavelet Neural Network[J].IEEE Transactions on Industry Applications, 2020, PP(99):1-1.DOI:10.1109/TIA.2020.3035131.