Closed-loop brain-machine interface system design based on improved single-joint information transmission model

被引:0
|
作者
Pan H.-G. [1 ]
Mi W.-Y. [1 ]
Deng J. [2 ]
Sun J.-G. [3 ]
Xue R. [3 ]
机构
[1] College of Electronic and Information Engineering, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi
[2] College of Safety Science and Engineering, Xi'an University of Science and Technology, Xi'an, 710054, Shaanxi
[3] Key Laboratory of Advanced Control and Optimization Technology of Ministry of Education, East China University of Science and Technology, Shanghai
来源
Kongzhi Lilun Yu Yingyong/Control Theory and Applications | 2020年 / 37卷 / 02期
基金
中国国家自然科学基金; 中国博士后科学基金;
关键词
Brain-machine interface; Closed-loop system; Decoder design; Model improvement; Model predictive control;
D O I
10.7641/CTA.2019.80619
中图分类号
学科分类号
摘要
In recent years, brain-machine interface (BMI) technology has been used more and more widely in physical rehabilitation and life support for the disabled and the elderly. For the single-joint information transmission (SJIT) model, through the model improvement, the decoder design and the auxiliary controller design, the closed-loop BMI system is formulated in this paper to restore the movement of the single joint. The innovation of this paper mainly includes: 1) the relative velocity vector is introduced to improve the SJIT model to reduce the overshoot, and then the performance of improved model is tested; 2) based on this improved model, a decoder based on Wiener filter and an auxiliary controller based on model predictive control strategy are designed and introduced to restore the missing information loop. The offline and online simulation results show that the improved model can greatly improve the output performance, reduce the overshoot clearly; and the formulated closed-loop system can well restore the missing information loop and track the target trajectory. In addition, the closed-loop system has strong anti-interference capability. © 2020, Editorial Department of Control Theory & Applications. All right reserved.
引用
收藏
页码:395 / 404
页数:9
相关论文
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