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Which is the best PID variant for pneumatic soft robots an experimental study

Ameer Hamza Khan, Zili Shao, Shuai Li Orcid Logo, Qixin Wang, Nan Guan

IEEE/CAA Journal of Automatica Sinica, Volume: 7, Issue: 2, Pages: 451 - 460

Swansea University Author: Shuai Li Orcid Logo

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DOI (Published version): 10.1109/jas.2020.1003045

Abstract

This paper presents an experimental study to compare the performance of model-free control strategies for pneumatic soft robots. Fabricated using soft materials, soft robots have gained much attention in academia and industry during recent years because of their inherent safety in human interaction....

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Published in: IEEE/CAA Journal of Automatica Sinica
ISSN: 2329-9266 2329-9274
Published: Institute of Electrical and Electronics Engineers (IEEE) 2020
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URI: https://cronfa.swan.ac.uk/Record/cronfa53870
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first_indexed 2020-03-27T13:35:19Z
last_indexed 2020-07-06T19:16:35Z
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spelling 2020-07-06T17:16:55.6114252 v2 53870 2020-03-27 Which is the best PID variant for pneumatic soft robots an experimental study 42ff9eed09bcd109fbbe484a0f99a8a8 0000-0001-8316-5289 Shuai Li Shuai Li true false 2020-03-27 MECH This paper presents an experimental study to compare the performance of model-free control strategies for pneumatic soft robots. Fabricated using soft materials, soft robots have gained much attention in academia and industry during recent years because of their inherent safety in human interaction. However, due to structural flexibility and compliance, mathematical models for these soft robots are nonlinear with an infinite degree of freedom (DOF). Therefore, accurate position (or orientation) control and optimization of their dynamic response remains a challenging task. Most existing soft robots currently employed in industrial and rehabilitation applications use model-free control algorithms such as PID. However, to the best of our knowledge, there has been no systematic study on the comparative performance of model-free control algorithms and their ability to optimize dynamic response, i.e., reduce overshoot and settling time. In this paper, we present comparative performance of several variants of model-free PID-controllers based on extensive experimental results. Additionally, most of the existing work on model-free control in pneumatic soft-robotic literature use manually tuned parameters, which is a time-consuming, labor-intensive task. We present a heuristic-based coordinate descent algorithm to tune the controller parameter automatically. We presented results for both manual tuning and automatic tuning using the Ziegler–Nichols method and proposed algorithm, respectively. We then used experimental results to statistically demonstrate that the presented automatic tuning algorithm results in high accuracy. The experiment results show that for soft robots, the PID-controller essentially reduces to the PI controller. This behavior was observed in both manual and automatic tuning experiments; we also discussed a rationale for removing the derivative term. Journal Article IEEE/CAA Journal of Automatica Sinica 7 2 451 460 Institute of Electrical and Electronics Engineers (IEEE) 2329-9266 2329-9274 Automatic tuning algorithm, model-free control, PID, soft robotics 1 3 2020 2020-03-01 10.1109/jas.2020.1003045 COLLEGE NANME Mechanical Engineering COLLEGE CODE MECH Swansea University 2020-07-06T17:16:55.6114252 2020-03-27T08:47:17.4074190 Ameer Hamza Khan 1 Zili Shao 2 Shuai Li 0000-0001-8316-5289 3 Qixin Wang 4 Nan Guan 5 53870__16977__abf5a2617fe5416caad6a943982cb3dc.pdf 53870.pdf 2020-03-30T15:38:41.7277565 Output 4660490 application/pdf Accepted Manuscript true false
title Which is the best PID variant for pneumatic soft robots an experimental study
spellingShingle Which is the best PID variant for pneumatic soft robots an experimental study
Shuai Li
title_short Which is the best PID variant for pneumatic soft robots an experimental study
title_full Which is the best PID variant for pneumatic soft robots an experimental study
title_fullStr Which is the best PID variant for pneumatic soft robots an experimental study
title_full_unstemmed Which is the best PID variant for pneumatic soft robots an experimental study
title_sort Which is the best PID variant for pneumatic soft robots an experimental study
author_id_str_mv 42ff9eed09bcd109fbbe484a0f99a8a8
author_id_fullname_str_mv 42ff9eed09bcd109fbbe484a0f99a8a8_***_Shuai Li
author Shuai Li
author2 Ameer Hamza Khan
Zili Shao
Shuai Li
Qixin Wang
Nan Guan
format Journal article
container_title IEEE/CAA Journal of Automatica Sinica
container_volume 7
container_issue 2
container_start_page 451
publishDate 2020
institution Swansea University
issn 2329-9266
2329-9274
doi_str_mv 10.1109/jas.2020.1003045
publisher Institute of Electrical and Electronics Engineers (IEEE)
document_store_str 1
active_str 0
description This paper presents an experimental study to compare the performance of model-free control strategies for pneumatic soft robots. Fabricated using soft materials, soft robots have gained much attention in academia and industry during recent years because of their inherent safety in human interaction. However, due to structural flexibility and compliance, mathematical models for these soft robots are nonlinear with an infinite degree of freedom (DOF). Therefore, accurate position (or orientation) control and optimization of their dynamic response remains a challenging task. Most existing soft robots currently employed in industrial and rehabilitation applications use model-free control algorithms such as PID. However, to the best of our knowledge, there has been no systematic study on the comparative performance of model-free control algorithms and their ability to optimize dynamic response, i.e., reduce overshoot and settling time. In this paper, we present comparative performance of several variants of model-free PID-controllers based on extensive experimental results. Additionally, most of the existing work on model-free control in pneumatic soft-robotic literature use manually tuned parameters, which is a time-consuming, labor-intensive task. We present a heuristic-based coordinate descent algorithm to tune the controller parameter automatically. We presented results for both manual tuning and automatic tuning using the Ziegler–Nichols method and proposed algorithm, respectively. We then used experimental results to statistically demonstrate that the presented automatic tuning algorithm results in high accuracy. The experiment results show that for soft robots, the PID-controller essentially reduces to the PI controller. This behavior was observed in both manual and automatic tuning experiments; we also discussed a rationale for removing the derivative term.
published_date 2020-03-01T04:07:04Z
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score 11.035874

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