A learning control scheme for upper-limb exoskeleton via adaptive sliding mode technique
This paper investigates an iterative learning approach integrated with sliding mode control method to accomplish passive rehabilitation therapy tasks for wearable 6 degrees of freedom (DOF) upper-limb exoskeleton. Firstly, the motion data of human body is collected from a healthy subject through VIC...
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| Published in | Mechatronics (Oxford) Vol. 86; p. 102832 |
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| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier Ltd
01.10.2022
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0957-4158 1873-4006 |
| DOI | 10.1016/j.mechatronics.2022.102832 |
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| Abstract | This paper investigates an iterative learning approach integrated with sliding mode control method to accomplish passive rehabilitation therapy tasks for wearable 6 degrees of freedom (DOF) upper-limb exoskeleton. Firstly, the motion data of human body is collected from a healthy subject through VICON motion capture system and reasonable trajectories in joint space are generated by fitting functions. Secondly, an iterative learning controller is developed to estimate the iteration-invariant dynamic parameters which are complicated and difficult to be obtained precisely in practice. Note that the identical initial condition (i.i.c) in traditional iterative learning control (ILC) is released by applying the polynomial reconstruction method. Considering the uncertainties and disturbances which affect the system in the form of friction, backlash and unexpected tissue torques from human body, an adaptive law is proposed to estimate the upper bound of the lumped non-periodic disturbances. Based on that, sliding mode controller is conducted to achieve the robustness over the time domain, while the chattering phenomenon is attenuated by applying tanh function. Afterwards, the stability and convergence of the overall system is rigorously proved with a composite energy function (CEF) composed of tracking and estimating errors. Finally, co-simulation and experiment results are presented to demonstrate the effectiveness of the proposed control scheme. |
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| AbstractList | This paper investigates an iterative learning approach integrated with sliding mode control method to accomplish passive rehabilitation therapy tasks for wearable 6 degrees of freedom (DOF) upper-limb exoskeleton. Firstly, the motion data of human body is collected from a healthy subject through VICON motion capture system and reasonable trajectories in joint space are generated by fitting functions. Secondly, an iterative learning controller is developed to estimate the iteration-invariant dynamic parameters which are complicated and difficult to be obtained precisely in practice. Note that the identical initial condition (i.i.c) in traditional iterative learning control (ILC) is released by applying the polynomial reconstruction method. Considering the uncertainties and disturbances which affect the system in the form of friction, backlash and unexpected tissue torques from human body, an adaptive law is proposed to estimate the upper bound of the lumped non-periodic disturbances. Based on that, sliding mode controller is conducted to achieve the robustness over the time domain, while the chattering phenomenon is attenuated by applying tanh function. Afterwards, the stability and convergence of the overall system is rigorously proved with a composite energy function (CEF) composed of tracking and estimating errors. Finally, co-simulation and experiment results are presented to demonstrate the effectiveness of the proposed control scheme. |
| ArticleNumber | 102832 |
| Author | Yang, Peng Guo, Shijie Zhang, Gaowei Wang, Jie |
| Author_xml | – sequence: 1 givenname: Gaowei orcidid: 0000-0002-2884-1325 surname: Zhang fullname: Zhang, Gaowei organization: College of Electronic Information and Automation, Civil Aviation University of China, No. 2898, Jinbei Road, Dongli District, Tianjin, 300300, Tianjin, China – sequence: 2 givenname: Jie orcidid: 0000-0002-8613-3976 surname: Wang fullname: Wang, Jie email: wang_jie@ustb.edu.cn organization: Institute of Artificial Intelligence, University of Science and Technology Beijing, No. 30 Xueyuan Road, Haidian District, Beijing, 100083, Beijing, China – sequence: 3 givenname: Peng orcidid: 0000-0003-3006-2184 surname: Yang fullname: Yang, Peng organization: School of Artificial Intelligence, Hebei University of Technology, No. 8 Guangrong Road, Hongqiao District, Tianjin, 300130, Tianjin, China – sequence: 4 givenname: Shijie surname: Guo fullname: Guo, Shijie organization: School of Mechanical Engineering, Hebei University of Technology, No. 8 Guangrong Road, Hongqiao District, Tianjin, 300130, Tianjin, China |
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| Keywords | Composite energy function (CEF) Sliding mode control (SMC) Iterative learning control (ILC) Co-simulation Upper-limb exoskeleton Trajectory reconstruction |
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| SubjectTerms | Co-simulation Composite energy function (CEF) Iterative learning control (ILC) Sliding mode control (SMC) Trajectory reconstruction Upper-limb exoskeleton |
| Title | A learning control scheme for upper-limb exoskeleton via adaptive sliding mode technique |
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