An adaptive seamless assist-as-needed control scheme for lower extremity rehabilitation robots
| Autor: | Xiaodong Zhang, Hanzhe Li, Gui Yin, Runlin Dong, Huosheng Hu |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Scheme (programming language)
0209 industrial biotechnology medicine.medical_specialty Computer science Mechanical Engineering Control (management) 02 engineering and technology Rehabilitation robot Gait cycle 020901 industrial engineering & automation Physical medicine and rehabilitation Assist as needed Control and Systems Engineering Rehabilitation training 0202 electrical engineering electronic engineering information engineering medicine Forgetting factor 020201 artificial intelligence & image processing computer Control methods computer.programming_language |
| Zdroj: | Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering. 235:723-734 |
| ISSN: | 2041-3041 0959-6518 |
| DOI: | 10.1177/0959651820970720 |
| Popis: | Most control methods deployed in lower extremity rehabilitation robots cannot automatically adjust to different gait cycle stages and different rehabilitation training modes for different impairment subjects. This article presents a continuous seamless assist-as-needed control method based on sliding mode adaptive control. A forgetting factor is introduced, and a small trajectory deviation from reference normal gait trajectory is used to learn the rehabilitation level of a human subject in real time. The assistance torque needed to complete the reference normal gait trajectory is learned through radial basis function neural networks, so that the rehabilitation robot can adaptively provide the assistance torque according to subject’s needs. The performance and efficiency of this adaptive seamless assist-as-needed control scheme are tested and validated by 12 volunteers on a rehabilitation robot prototype. The results show that the proposed control scheme could adaptively reduce the robotic assistance according to subject’s rehabilitation level, and the robotic assistance torque depends on the forgetting factor and the active participation level of subjects. |
| Databáze: | OpenAIRE |
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