NDLI: Impedance estimation of a pneumatic muscle as a mechanical transmission and actuation device

Content Provider	IEEE Xplore Digital Library
Author	Prasad, Prem Kumar Sen, Soumen Shome, S.N Har, Chandan
Copyright Year	2016
Description	Author affiliation: Robotics and Automation, CSIR-CMERI, Durgapur, India (Sen, Soumen; Shome, S.N; Har, Chandan) \|\| School of Mechatronics and Robotics, IIEST, Shibpur Howah, India (Prasad, Prem Kumar)
Abstract	Human friendly robots and devices like exoskeletons, active prostheses etc. are required to be compliant in their actuation system; here the transmissions are deliberately made flexible. This flexibility demands variability in order to improve upon the transmission bandwidth, as well as meeting specific requirements in task execution. Pneumatic Muscle Actuator (PMA) has an inherent ability to vary impedance of transmission in its actuation with varying pressure, resembling a biological muscle, when implemented in agonist-antagonistic arrangement. Regulation and control for stiffness/impedance requires knowledge of the impedance values; however, there is no transducer available to measure the impedance components. In this paper the issue of online estimation of impedance components of a pneumatic muscle actuator is addressed in terms of effective inertia, damping rate and stiffness of the elastic muscle. Devising a model free estimator is indeed difficult, especially in steady state. The present approach considers a physical model of the Pneumatic Artificial Muscle (PAM), suitable for practical implementation and in the same time detailed enough representing, as far as possible, all important behaviors (relating muscle force with displacement/contraction, muscle velocity and muscle pressure). Sensors with noise and varying behavior of passive components with time (and environment) can provide only approximate calibration with inconsistent and not-so-stable results. Online estimation becomes necessary here. This article proposes a first order Extended Kalman Filtering technique to estimate online the impedance parameters. Experimental results are presented to validate the proposed estimation algorithm.
Starting Page	371
Ending Page	375
File Size	1076660
Page Count	5
File Format	PDF
e-ISBN	9781479917693
DOI	10.1109/CMI.2016.7413773
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2016-01-08
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Force Extended Kalman Filter Flexible Transmission Estimation Muscles Variable Stiffness/Impedance Actuation Impedance Estimation Pneumatic Artificial Muscles Impedance Kalman filters Force sensors
Content Type	Text
Resource Type	Article

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