Hysteresis Modeling of a PAM System Using ANFIS

Pneumatic artificial muscles (PAMs) are excellent environmentally friendly actuators and springs that remain somewhat underutilized in the industry due to their hysteretic behavior, which makes predicting their behavior difficult. This paper presents a novel black-box approach that employs an adapti...

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Autores principales:	Saad Abu Mohareb, Adham Alsharkawi, Moudar Zgoul
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	PAMs ANFIS hysteresis modeling control FESTO Materials of engineering and construction. Mechanics of materials TA401-492 Production of electric energy or power. Powerplants. Central stations TK1001-1841
Acceso en línea:	https://doaj.org/article/8eec13b5d0d84f38861e5c29baf87e3f
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spelling	oai:doaj.org-article:8eec13b5d0d84f38861e5c29baf87e3f2021-11-25T15:56:46ZHysteresis Modeling of a PAM System Using ANFIS10.3390/act101102802076-0825https://doaj.org/article/8eec13b5d0d84f38861e5c29baf87e3f2021-10-01T00:00:00Zhttps://www.mdpi.com/2076-0825/10/11/280https://doaj.org/toc/2076-0825Pneumatic artificial muscles (PAMs) are excellent environmentally friendly actuators and springs that remain somewhat underutilized in the industry due to their hysteretic behavior, which makes predicting their behavior difficult. This paper presents a novel black-box approach that employs an adaptive-network-based fuzzy inference system (ANFIS) to create pressure-contraction hysteresis models. The resulting models are simulated in a control system toolbox to test their controllability using a simple proportional-integral (PI) controller. The data showed that the models created based on fixed inputs had an average normalized root mean square error (RMSE) of 0.0327, and their generalized counterparts achieved an average normalized RMSE of 0.04087. The simulation results showed that the PI controller was able to achieve mean tracking errors of 8.1 µm and 18.3 µm when attempting to track a sinusoidal and step references, respectively. This work concludes that modeling using the ANFIS is limited to being able to know the derivative of the input pressure or its rate of change, but competently models hysteresis in PAMs across multiple operating ranges. This is the highlight of this work. Additionally, these ANFIS-created models lend themselves well to controller, but exploring more refined control schemes is necessary to fully utilize them.Saad Abu MoharebAdham AlsharkawiMoudar ZgoulMDPI AGarticlePAMsANFIShysteresismodelingcontrolFESTOMaterials of engineering and construction. Mechanics of materialsTA401-492Production of electric energy or power. Powerplants. Central stationsTK1001-1841ENActuators, Vol 10, Iss 280, p 280 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	PAMs ANFIS hysteresis modeling control FESTO Materials of engineering and construction. Mechanics of materials TA401-492 Production of electric energy or power. Powerplants. Central stations TK1001-1841
spellingShingle	PAMs ANFIS hysteresis modeling control FESTO Materials of engineering and construction. Mechanics of materials TA401-492 Production of electric energy or power. Powerplants. Central stations TK1001-1841 Saad Abu Mohareb Adham Alsharkawi Moudar Zgoul Hysteresis Modeling of a PAM System Using ANFIS
description	Pneumatic artificial muscles (PAMs) are excellent environmentally friendly actuators and springs that remain somewhat underutilized in the industry due to their hysteretic behavior, which makes predicting their behavior difficult. This paper presents a novel black-box approach that employs an adaptive-network-based fuzzy inference system (ANFIS) to create pressure-contraction hysteresis models. The resulting models are simulated in a control system toolbox to test their controllability using a simple proportional-integral (PI) controller. The data showed that the models created based on fixed inputs had an average normalized root mean square error (RMSE) of 0.0327, and their generalized counterparts achieved an average normalized RMSE of 0.04087. The simulation results showed that the PI controller was able to achieve mean tracking errors of 8.1 µm and 18.3 µm when attempting to track a sinusoidal and step references, respectively. This work concludes that modeling using the ANFIS is limited to being able to know the derivative of the input pressure or its rate of change, but competently models hysteresis in PAMs across multiple operating ranges. This is the highlight of this work. Additionally, these ANFIS-created models lend themselves well to controller, but exploring more refined control schemes is necessary to fully utilize them.
format	article
author	Saad Abu Mohareb Adham Alsharkawi Moudar Zgoul
author_facet	Saad Abu Mohareb Adham Alsharkawi Moudar Zgoul
author_sort	Saad Abu Mohareb
title	Hysteresis Modeling of a PAM System Using ANFIS
title_short	Hysteresis Modeling of a PAM System Using ANFIS
title_full	Hysteresis Modeling of a PAM System Using ANFIS
title_fullStr	Hysteresis Modeling of a PAM System Using ANFIS
title_full_unstemmed	Hysteresis Modeling of a PAM System Using ANFIS
title_sort	hysteresis modeling of a pam system using anfis
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/8eec13b5d0d84f38861e5c29baf87e3f
work_keys_str_mv	AT saadabumohareb hysteresismodelingofapamsystemusinganfis AT adhamalsharkawi hysteresismodelingofapamsystemusinganfis AT moudarzgoul hysteresismodelingofapamsystemusinganfis
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Hysteresis Modeling of a PAM System Using ANFIS

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