Adaptive Iterative Learning Control design for RUPERT IV

An adaptive robot control strategy combining PID-based feedback and Iterative Learning Controller (ILC) is proposed for performing passive reaching tasks for RUPERTtrade (Robotic Upper Extremity Repetitive Therapy), a pneumatic muscle driven rehabilitation robotic device. Additionally, a fuzzy rule-...

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Bibliographic Details
Published in:2008 2nd IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics pp. 647 - 652
Main Authors: Ruihua Wei, Balasubramanian, S., Lihong Xu, Jiping He
Format: Conference Proceeding
Language:English
Published: IEEE 01.10.2008
Subjects:
Adaptive control
Control design
Extremities
Feedback
Fuzzy Rule-Base
Iterative Learning Control
Medical treatment
Muscles
Pneumatic Muscle Actuator
Programmable control
Rehabilitation robotics
Robot control
Testing
Upper Extremity
ISBN:9781424428823, 1424428823
ISSN:2155-1774
Online Access:Get full text
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Summary:An adaptive robot control strategy combining PID-based feedback and Iterative Learning Controller (ILC) is proposed for performing passive reaching tasks for RUPERTtrade (Robotic Upper Extremity Repetitive Therapy), a pneumatic muscle driven rehabilitation robotic device. Additionally, a fuzzy rule-base is used to estimate the ILC learning rate to achieve an optimized learning. The preliminary test results from two able-bodied subjects demonstrate that the proposed controller can provide consistent performance for different subjects performing different reaching tasks.
ISBN:9781424428823
1424428823
ISSN:2155-1774
DOI:10.1109/BIOROB.2008.4762841