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Neural-Network Inverse Dynamic Online Learning Control on Physical Exoskeleton
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Control and Robotics
Neural-Network Inverse Dynamic Online Learning Control on Physical Exoskeleton
Heng Cao1 , Yuhai Yin1, Ding Du1, Lizong Lin1, Wenjin Gu2 and Zhiyong Yang2
| (1) |
East China University of Science and Technology, School of Mechanical and Power, Engineering, Postbox: 401. Postcode: 200237.
Shanghai, China |
| (2) |
Navy Aeronautical Engineering College, Department of Control Engineering. Yantai, Shandong province, China |
Abstract
Exoskeleton system which is to assist the motion of physically weak persons such as disabled, injured and elderly persons
is discussed in this paper. The proposed exoskeletons are controlled basically based on the electromoyogram (EMG) signals.
And a mind model is constructed to identify person’s mind for predicting or estimating person’s behavior. The proposed mind
model is installed in an exoskeleton power assistive system named IAE for walking aid. The neural-network is also be used
in this system to help learning. The on-line learning adjustment algorithm based on multi-sensor that are fixed on the robot
is designed which makes the locomotion stable and adaptable.
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