Passivity based adaptive control for upper extremity assist exoskeleton

Upper limb assist exoskeleton robot requires quantitative techniques to assess human motor function and generate command signal for robots to act in compliance with human motion. To asses human motor function, we present Desired Motion Intention (DMI) estimation algorithm using Muscle Circumference...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of control, automation, and systems Vol. 14; no. 1; pp. 291 - 300
Main Authors Khan, Abdul Manan, Yun, Deok-won, Ali, Mian Ashfaq, Zuhaib, Khalil Muhammad, Yuan, Chao, Iqbal, Junaid, Han, Jungsoo, Shin, Kyoosik, Han, Changsoo
Format Journal Article
LanguageEnglish
Published Bucheon / Seoul Institute of Control, Robotics and Systems and The Korean Institute of Electrical Engineers 01.02.2016
Springer Nature B.V
제어·로봇·시스템학회
Subjects
Online AccessGet full text
ISSN1598-6446
2005-4092
DOI10.1007/s12555-014-0250-x

Cover

More Information
Summary:Upper limb assist exoskeleton robot requires quantitative techniques to assess human motor function and generate command signal for robots to act in compliance with human motion. To asses human motor function, we present Desired Motion Intention (DMI) estimation algorithm using Muscle Circumference Sensor (MCS) and load cells. Here, MCS measures human elbow joint torque using human arm kinematics, biceps/triceps muscle model and physiological cross sectional area of these muscles whereas load cells play a compensatory role for the torque generated by shoulder muscles as these cells measure desire of shoulder muscles to move the arm and not the internal activity of shoulder muscles. Furthermore, damped least square algorithm is used to estimate Desired Motion Intention (DMI) from these torques. To track this estimated DMI, we have used passivity based adaptive control algorithm. This control techniques is particular useful to adapt modeling error of assist exoskeleton robot for different subjects. Proposed methodology is experimentally evaluated on seven degree of freedom upper limb assist exoskeleton. Results show that DMI is well estimated and tracked for assistance by the proposed control algorithm.
Bibliography:SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 14
ObjectType-Article-1
ObjectType-Feature-2
content type line 23
http://link.springer.com/article/10.1007/s12555-014-0250-x
G704-000903.2016.14.1.009
ISSN:1598-6446
2005-4092
DOI:10.1007/s12555-014-0250-x