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JACIII Vol.23 No.2 pp. 183-195
doi: 10.20965/jaciii.2019.p0183
(2019)

Paper:

Interaction Forces Identification Modeling and Tracking Control for Rehabilitative Training Walker

Ping Sun*, Wenjiao Zhang*, Shuoyu Wang**, and Hongbin Chang**

*School of Information Science and Engineering, Shenyang University of Technology
No.111 Shenliao West Road, Shenyang 110870, China

**Department of Intelligent Mechanical Systems Engineering, Kochi University of Technology
185 Miyanokuchi, Tosayamada, Kami, Kochi 782-8502, Japan

Received:
April 23, 2018
Accepted:
October 2, 2018
Published:
March 20, 2019
Keywords:
omnidirectional walker, interaction forces, fuzzy identification modeling, adaptive backstepping control
Abstract
Interaction Forces Identification Modeling and Tracking Control for Rehabilitative Training Walker

The rehabilitative walker can help patients undergoing training move in any direction on a flat surface, and can be programmed to follow specific training trajectories

In this study, we propose a model and an adaptive backstepping tracking control method for omnidirectional rehabilitative training walker. The aim of the study is to design a stable tracking controller that can guarantee accurate tracking motion of the omnidirectional walker considering the interaction forces of the user and walker. A novel fuzzy model identification method was proposed to describe the interaction forces by using the reduced values of tracking performance. Further, an adaptive backstepping controller was developed to compensate the interaction forces on the basis of the identified model and adapt the change of user’s mass. The asymptotic stability of the trajectory tracking error and the velocity tracking error were guaranteed. As an application, simulation and experiment results were provided to illustrate the effectiveness of the proposed design procedures.

Cite this article as:
P. Sun, W. Zhang, S. Wang, and H. Chang, “Interaction Forces Identification Modeling and Tracking Control for Rehabilitative Training Walker,” J. Adv. Comput. Intell. Intell. Inform., Vol.23, No.2, pp. 183-195, 2019.
Data files:
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Last updated on Aug. 21, 2019