Design and control strategy of 3-prismatic-revolute-spherical ankle rehabilitation robot

ABSTRACT

Aiming at the position and pose control requirement of the ankle rehabilitation robot, two schemes of 3-PRS (Prismatic-Revolute-Spherical) parallel ankle rehabilitation robots are proposed, and the analysis and simulation of the control strategy are carried out. Two schemes of 3-PRS ankle rehabilitation robots are statically analysed by the finite element method. Through the stress comparison of the two schemes, the stable one is determined. Three control strategies including the traditional PID control, PID control based on the genetic algorithm and adaptive fuzzy PID control are proposed. A multidisciplinary co-simulation platform is established by the combination of ADAMS, SOLIDWORKS and MATLAB, and the three control strategies are verified. The best control strategy for the rehabilitation robots is determined by comparing control effects. This study lays a solid foundation for research on the control of the rehabilitation robots.

KEYWORDS:

• 3-PRS parallel robot
• ankle rehabilitation
• finite element
• inverse kinematic
• fuzzy control

Nomenclature

Table

Acknowledgments

The authors also gratefully acknowledge the helpful comments and suggestions of the reviewers, which have improved the presentation.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available in re3data.org at http://doi.org/10.7277/FC3T-ME71, reference number 17214273.

Additional information

Funding

This work is partially supported by the Key Technology R&D Program of Henan Province of China [No. 212102210045, No. 182102310706], the Fundamental Research Funds for the Universities of Henan Province [No. NSFRF200401] and National Natural Science Foundation of China [No. U1304525].

Notes on contributors

Guoqiang Chen

Guoqiang Chen received the PhD degree from Tongji University, China. He is currently working as a Professor in School of Mechanical and Power Engineering, at Henan Polytechnic University, China. His research focuses on robot technology, automobile technology and artificial intelligence.

Zhuangzhuang Mao

Zhuangzhuang Mao is a Master student in School of Mechanical and Power Engineering, at Henan Polytechnic University, China. His research focuses on robot technology and artificial intelligence.

Hongpeng Zhou

Hongpeng Zhou is a Master student in School of Mechanical and Power Engineering, at Henan Polytechnic University, China. His research focuses on robot technology and artificial intelligence. 

Pengcheng Yang

Pengcheng Yang is a Master student in School of Mechanical and Power Engineering, at Henan Polytechnic University, China. His research focuses on robot technology and control.