An advanced bionic knee joint mechanism with neural network controller

Changxian Xu; Zhongbo Sun; Chen Wang; Xiujun Wu; Binglin Li; Liming Zhao

doi:10.3389/fnbot.2023.1178006

An advanced bionic knee joint mechanism with neural network controller

Front Neurorobot. 2023 May 5:17:1178006. doi: 10.3389/fnbot.2023.1178006. eCollection 2023.

Authors

Changxian Xu¹, Zhongbo Sun¹, Chen Wang¹, Xiujun Wu¹, Binglin Li¹, Liming Zhao¹

Affiliation

¹ Department of Control Engineering, Changchun University of Technology, Changchun, China.

Abstract

In this article, a tensegrity-based knee mechanism is studied for developing a high-efficiency rehabilitation knee exoskeleton. Moreover, the kinematics and dynamics models of the knee mechanism are explored for bringing about further improvement in controller design. In addition, to estimate the performance of the bionic knee joint, based on the limit function of knee patella, the limit position functionality of the bionic knee joint is developed for enhancing the bionic property. Furthermore, to eliminate the noise item and other disturbances that are constantly generated in the rehabilitation process, a noise-tolerant zeroing neural network (NTZNN) algorithm is utilized to establish the controller. This indicates that the controller shows an anti-noise performance; hence, it is quite unique from other bionic knee mechanism controllers. Eventually, the anti-noise performance and the calculation of the precision of the NTZNN controller are verified through several simulation and contrast results.

Keywords: bionic knee joint; dynamics; kinematics; noise-tolerant zeroing neural network model; tensegrity.

Grants and funding

This work was supported in parts by the National Natural Science Foundation of China under grants 61873304, 62173048, and 62106023, the Innovation and Entrepreneurship Talent Funding Project of Jilin Province 2022QN04, and the Changchun Science and Technology Project under grant 21ZY41.