Estimation of the human motion without using biologically measured signals and its application to the control of the wearable power assist suit

2017 Fiscal Year Final Research Report

• Project/Area Number: 26420200
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Research Field: Intelligent mechanics/Mechanical systems
• Research Institution: Yamaguchi University
• Principal Investigator: FUJII Fumitake 山口大学, 大学院創成科学研究科, 准教授 (30274179)
• Project Period (FY): 2014-04-01 – 2018-03-31
• Keywords: 外骨格型パワーアシストスーツ / 負荷推定器 / ロジスティック識別器 / 適応スライディングモード制御 / MCSモデル規範適応制御 / カルマンフィルタ

Outline of Final Research Achievements

The current study focuses on the control system designs for the powered exoskeleton which does not use the biologically measured signal. We have synthesized two different control systems. One concentrates on the in-phase tracking to human body motion and the other tries to provide sufficient force/torque to the user of the exoskeleton. The former uses the adaptive Kalman filter to estimate angular acceleration of the joints supported by the exoskeleton under the existence of the model uncertainty and the sensor offset, and the adaptive sliding mode controller has been implemented for the control of the actuator to achieve in-phase tracking to human motion. The second one includes the development of load estimator which utilizes the quantitative difference of the body usage which depends on the amount of load. The MCS adaptive controller will follow to provide the sufficient force/torque support to the user. Experimental results show the validity of the proposed control system.

Free Research Field

人間機械システム