Hysteresis Compensation of 3D Printed Sensors Using a Power Law Model for Various Input Signals

Martijn  Schouten; Dimitrios  Kosmas; Gijs Krijnen

doi:10.1109/SENSORS47125.2020.9278942

Hysteresis Compensation of 3D Printed Sensors Using a Power Law Model for Various Input Signals

Martijn Schouten, Dimitrios Kosmas, Gijs Krijnen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

5 Citations (Scopus)

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Abstract

We calculated the stability criterion for the modified power law model and subsequently adjust the model such that it’s stability can be guaranteed. We applied both a sinusoid, a chirp, an exponentially decaying sine and bandwidth limited noise position excitation to a 3D printed symmetric piezoresistive cantilever and measure the differential response. A modified power law model is fitted directly to the inverse of the sensor data, to directly obtain a compensator for the sensor. The result was a stable compensator that reduced the hysteresis of the 3D printed sensor.

Original language	English
Title of host publication	2020 IEEE Sensors
Publisher	IEEE
ISBN (Electronic)	978-1-7281-6801-2
ISBN (Print)	978-1-7281-6802-9
DOIs	https://doi.org/10.1109/SENSORS47125.2020.9278942
Publication status	Published - 9 Dec 2020
Event	IEEE Sensors 2020 - Virtual Event, Virtual, Rotterdam, Netherlands Duration: 25 Oct 2020 → 28 Oct 2020 https://2020.ieee-sensorsconference.org/

Conference

Conference	IEEE Sensors 2020
Country/Territory	Netherlands
City	Virtual, Rotterdam
Period	25/10/20 → 28/10/20
Internet address	https://2020.ieee-sensorsconference.org/

Keywords

3D printing
Hysteresis
Compensation
Flexible
Soft
Tactile sensor
Power Law
Non-linear
Stability
Recurrent
Shallow
Neural network

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10.1109/SENSORS47125.2020.9278942

ArticleAccepted author version, 1.05 MBLicence: CC BY

Cite this

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title = "Hysteresis Compensation of 3D Printed Sensors Using a Power Law Model for Various Input Signals",

abstract = "We calculated the stability criterion for the modified power law model and subsequently adjust the model such that it{\textquoteright}s stability can be guaranteed. We applied both a sinusoid, a chirp, an exponentially decaying sine and bandwidth limited noise position excitation to a 3D printed symmetric piezoresistive cantilever and measure the differential response. A modified power law model is fitted directly to the inverse of the sensor data, to directly obtain a compensator for the sensor. The result was a stable compensator that reduced the hysteresis of the 3D printed sensor.",

keywords = "3D printing, Hysteresis, Compensation, Flexible, Soft, Tactile sensor, Power Law, Non-linear, Stability, Recurrent, Shallow, Neural network",

author = "Martijn Schouten and Dimitrios Kosmas and Gijs Krijnen",

note = "Funding Information: This work was developed within the Wearable Robotics programme, funded by the Dutch Research Council (NWO). Publisher Copyright: {\textcopyright} 2020 IEEE.; IEEE Sensors 2020 ; Conference date: 25-10-2020 Through 28-10-2020",

year = "2020",

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AU - Kosmas, Dimitrios

AU - Krijnen, Gijs

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Y1 - 2020/12/9

N2 - We calculated the stability criterion for the modified power law model and subsequently adjust the model such that it’s stability can be guaranteed. We applied both a sinusoid, a chirp, an exponentially decaying sine and bandwidth limited noise position excitation to a 3D printed symmetric piezoresistive cantilever and measure the differential response. A modified power law model is fitted directly to the inverse of the sensor data, to directly obtain a compensator for the sensor. The result was a stable compensator that reduced the hysteresis of the 3D printed sensor.

AB - We calculated the stability criterion for the modified power law model and subsequently adjust the model such that it’s stability can be guaranteed. We applied both a sinusoid, a chirp, an exponentially decaying sine and bandwidth limited noise position excitation to a 3D printed symmetric piezoresistive cantilever and measure the differential response. A modified power law model is fitted directly to the inverse of the sensor data, to directly obtain a compensator for the sensor. The result was a stable compensator that reduced the hysteresis of the 3D printed sensor.

KW - 3D printing

KW - Hysteresis

KW - Compensation

KW - Flexible

KW - Soft

KW - Tactile sensor

KW - Power Law

KW - Non-linear

KW - Stability

KW - Recurrent

KW - Shallow

KW - Neural network

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DO - 10.1109/SENSORS47125.2020.9278942

M3 - Conference contribution

SN - 978-1-7281-6802-9

BT - 2020 IEEE Sensors

PB - IEEE

T2 - IEEE Sensors 2020

Y2 - 25 October 2020 through 28 October 2020

ER -

Hysteresis Compensation of 3D Printed Sensors Using a Power Law Model for Various Input Signals

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