Joint Motion Control for Lower Limb Rehabilitation Based on Iterative Learning Control (ILC) Algorithm
At present, the motion control algorithms of lower limb exoskeleton robots have errors in tracking the desired trajectory of human hip and knee joints, which leads to poor follow-up performance of the human-machine system. Therefore, an iterative learning control algorithm is proposed to track the d...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/6651495 |
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| author | Wei Guan Lan Zhou YouShen Cao |
| author_facet | Wei Guan Lan Zhou YouShen Cao |
| author_sort | Wei Guan |
| collection | DOAJ |
| description | At present, the motion control algorithms of lower limb exoskeleton robots have errors in tracking the desired trajectory of human hip and knee joints, which leads to poor follow-up performance of the human-machine system. Therefore, an iterative learning control algorithm is proposed to track the desired trajectory of human hip and knee joints. In this paper, the experimental platform of lower limb exoskeleton rehabilitation robot is built, and the control system software and hardware design and robot prototype function test are carried out. On this basis, a series of experiments are carried out to verify the rationality of the robot structure and the feasibility of the control method. Firstly, the dynamic model of the lower limb exoskeleton robot is established based on the structure analysis of the human lower limb; secondly, the servo control model of the lower limb exoskeleton robot is established based on the iterative learning control algorithm; finally, the exponential gain closed-loop system is designed by using MATLAB software. The relationship between convergence speed and spectral radius is analyzed, and the expected trajectory of hip joint and knee joint is obtained. The simulation results show that the algorithm can effectively improve the gait tracking accuracy of the lower limb exoskeleton robot and improve the follow-up performance of the human-machine system. |
| format | Article |
| id | doaj-art-8b44c6b139794bf89e8209f24d7ffe62 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-8b44c6b139794bf89e8209f24d7ffe622025-02-03T06:07:36ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/66514956651495Joint Motion Control for Lower Limb Rehabilitation Based on Iterative Learning Control (ILC) AlgorithmWei Guan0Lan Zhou1YouShen Cao2Department of Physical Education, Northwest University, Xi’an 710127, ChinaDepartment of Physical Education, Northwest University, Xi’an 710127, ChinaCollege of Arts and Sports, Dong-A University, Busan 49315, Republic of KoreaAt present, the motion control algorithms of lower limb exoskeleton robots have errors in tracking the desired trajectory of human hip and knee joints, which leads to poor follow-up performance of the human-machine system. Therefore, an iterative learning control algorithm is proposed to track the desired trajectory of human hip and knee joints. In this paper, the experimental platform of lower limb exoskeleton rehabilitation robot is built, and the control system software and hardware design and robot prototype function test are carried out. On this basis, a series of experiments are carried out to verify the rationality of the robot structure and the feasibility of the control method. Firstly, the dynamic model of the lower limb exoskeleton robot is established based on the structure analysis of the human lower limb; secondly, the servo control model of the lower limb exoskeleton robot is established based on the iterative learning control algorithm; finally, the exponential gain closed-loop system is designed by using MATLAB software. The relationship between convergence speed and spectral radius is analyzed, and the expected trajectory of hip joint and knee joint is obtained. The simulation results show that the algorithm can effectively improve the gait tracking accuracy of the lower limb exoskeleton robot and improve the follow-up performance of the human-machine system.http://dx.doi.org/10.1155/2021/6651495 |
| spellingShingle | Wei Guan Lan Zhou YouShen Cao Joint Motion Control for Lower Limb Rehabilitation Based on Iterative Learning Control (ILC) Algorithm Complexity |
| title | Joint Motion Control for Lower Limb Rehabilitation Based on Iterative Learning Control (ILC) Algorithm |
| title_full | Joint Motion Control for Lower Limb Rehabilitation Based on Iterative Learning Control (ILC) Algorithm |
| title_fullStr | Joint Motion Control for Lower Limb Rehabilitation Based on Iterative Learning Control (ILC) Algorithm |
| title_full_unstemmed | Joint Motion Control for Lower Limb Rehabilitation Based on Iterative Learning Control (ILC) Algorithm |
| title_short | Joint Motion Control for Lower Limb Rehabilitation Based on Iterative Learning Control (ILC) Algorithm |
| title_sort | joint motion control for lower limb rehabilitation based on iterative learning control ilc algorithm |
| url | http://dx.doi.org/10.1155/2021/6651495 |
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