Active multimode vibration control of a smart structure using macro fiber composite actuators based on ANFIS

In this study, vibration control was achieved using macro fiber composite actuators initiated by feedback from polyvinylidene difluoride (PVDF) membrane sensors. First, the structure mode was found using the finite element method after which simulation of the effect of piezoelectric actuators on the...

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Main Authors: Wen-Lin Chu, Chih-Jer Lin, Ming-Jia Li
Format: Article
Language:English
Published: SAGE Publishing 2020-12-01
Series:Journal of Low Frequency Noise, Vibration and Active Control
Online Access:https://doi.org/10.1177/1461348419872305
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spelling doaj-c0cecac945064e5e9a50980b32b5ec7d2020-12-10T04:04:09ZengSAGE PublishingJournal of Low Frequency Noise, Vibration and Active Control1461-34842048-40462020-12-013910.1177/1461348419872305Active multimode vibration control of a smart structure using macro fiber composite actuators based on ANFISWen-Lin ChuChih-Jer LinMing-Jia LiIn this study, vibration control was achieved using macro fiber composite actuators initiated by feedback from polyvinylidene difluoride (PVDF) membrane sensors. First, the structure mode was found using the finite element method after which simulation of the effect of piezoelectric actuators on the structure as well as a feasibility investigation was carried out. The ANSYS Workbench was used for parametric design and to determine the best position for the actuators. Structure vibration in different modes was measured using PVDF membrane sensors for feedback control and to investigate the vibration reduction effect achieved with three individual controllers. The pros and cons of active vibration reduction control were also examined in several different modes. The experimental results obtained with several types of vibration reduction control were compared: Type-1 fuzzy control, Type-1 adaptive fuzzy control, and the vibration reduction effect of an adaptive neuro-fuzzy inference system. The results showed that the adaptive neuro-fuzzy inference system controller was the best choice under the experimental conditions used in this study.https://doi.org/10.1177/1461348419872305
collection DOAJ
language English
format Article
sources DOAJ
author Wen-Lin Chu
Chih-Jer Lin
Ming-Jia Li
spellingShingle Wen-Lin Chu
Chih-Jer Lin
Ming-Jia Li
Active multimode vibration control of a smart structure using macro fiber composite actuators based on ANFIS
Journal of Low Frequency Noise, Vibration and Active Control
author_facet Wen-Lin Chu
Chih-Jer Lin
Ming-Jia Li
author_sort Wen-Lin Chu
title Active multimode vibration control of a smart structure using macro fiber composite actuators based on ANFIS
title_short Active multimode vibration control of a smart structure using macro fiber composite actuators based on ANFIS
title_full Active multimode vibration control of a smart structure using macro fiber composite actuators based on ANFIS
title_fullStr Active multimode vibration control of a smart structure using macro fiber composite actuators based on ANFIS
title_full_unstemmed Active multimode vibration control of a smart structure using macro fiber composite actuators based on ANFIS
title_sort active multimode vibration control of a smart structure using macro fiber composite actuators based on anfis
publisher SAGE Publishing
series Journal of Low Frequency Noise, Vibration and Active Control
issn 1461-3484
2048-4046
publishDate 2020-12-01
description In this study, vibration control was achieved using macro fiber composite actuators initiated by feedback from polyvinylidene difluoride (PVDF) membrane sensors. First, the structure mode was found using the finite element method after which simulation of the effect of piezoelectric actuators on the structure as well as a feasibility investigation was carried out. The ANSYS Workbench was used for parametric design and to determine the best position for the actuators. Structure vibration in different modes was measured using PVDF membrane sensors for feedback control and to investigate the vibration reduction effect achieved with three individual controllers. The pros and cons of active vibration reduction control were also examined in several different modes. The experimental results obtained with several types of vibration reduction control were compared: Type-1 fuzzy control, Type-1 adaptive fuzzy control, and the vibration reduction effect of an adaptive neuro-fuzzy inference system. The results showed that the adaptive neuro-fuzzy inference system controller was the best choice under the experimental conditions used in this study.
url https://doi.org/10.1177/1461348419872305
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