Force sensorless admittance control of body weight support system

Abstract

The effectiveness of rehabilitation treatment with the Body Weight Support (BWS) system has been demonstrated in patients with stroke and spinal cord injury. Many recent studies used expensive force sensors to realize the force control, which plays an important role in a BWS system. To reduce the system cost and complexity, and overcome some shortcomings of force sensors like measurement noise and lag, a force sensorless admittance control method is proposed. Then, an active BWS platform has been designed to verify the effect of the sensorless control method. The robust stability of the BWS system was proved through the small gain theorem. Human walking experiments assisted by the BWS system were conducted. It turns out that the estimated force is in close agreement with the value measured by the force sensor. The proposed controller achieved a control deviation of less than 10% around a desired mass offload during the experiments. It was validated effective for the proposed controller in accurate force control.

GRAPHICAL ABSTRACT

Keywords:

• BWS system
• force estimation
• admittance control
• stability analysis
• small gain theorem

Disclosure statement

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

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant Number U1913207, and Joint Fund of Science & Technology Department of Liaoning Province and State Key Laboratory of Robotics, China.

Notes on contributors

Jun Huo

Jun Huo received his B.E. degree from the Northeast University in 2018. He is currently a postgraduate student in Huazhong University of Science and Technology, Wuhan, China. His research interests include rehabilitation exoskeleton robotics and force control.

Jian Huang

Jian Huang received his B.E., M.E. and PhD degrees from Huazhong University of Science and Technology (HUST), Wuhan, China, in 1997, 2000 and 2005, respectively. From 2006 to 2008, he was a Postdoctoral Researcher at the Department of Micro- Nano System Engineering and the Department of Mechano-Informatics and Systems, Nagoya University, Japan. He is currently a Full Professor with the School of Artificial Intelligence and Automation, HUST. His main research interests include rehabilitation robot, robotic assembly, networked control systems and bioinformatics. He is serving as the Associate Editor of IEEE Transactions on Fuzzy Systems.

Xikai Tu

Xikai Tu received the M.Sc. degree in biomedical engineering and the PhD degree in control science and engineering from the Huazhong University of Science and Technology, China, in 2011 and 2016, respectively. He is currently an Assistant Professor with the School of Mechanical Engineering, Hubei University of Technology, Wuhan, China. His research interests include the development of rehabilitation strategies for both robotics and functional electrical stimulation targeted at post-stroke limb rehabilitation to realize ADLs and natural gait.

Zhongzheng Fu

Zhongzheng Fu received his B.S. and M.S. degrees from the Chongqing University of Technology in 2015, 2018, respectively. In 2017, he worked at Tohoku University as a collaborative researcher. In 2019, he worked at Chongqing University of Technology. Since 2020, he has been a research assistant at Huazhong University of Science and Technology. His research interests include human activity recognition, exoskeleton robotic systems, pneumatic muscle actuators, and membrane computing.