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    Neural Networks Based Active Vibration Control of Flexible Linkage Mechanisms

    Source: Journal of Mechanical Design:;2001:;volume( 123 ):;issue: 002::page 266
    Author:
    Y. M. Song
    ,
    Postdoctor
    ,
    C. Zhang
    ,
    Y. Q. Yu
    DOI: 10.1115/1.1348269
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: An investigation is presented into the neural networks based active vibration control of flexible linkage mechanisms. A smart mechanism featuring piezoceramic actuators and strain gauge sensors is designed. A nonlinear adaptive control strategy named Neural Networks based Direct Self-Tuning Control (NNBDSC) is employed to suppress the elastodynamic responses of the smart mechanism. To improve the initial robustness of the NNBDSC, the Dynamic Recurrent Neural Network (DRNN) controllers are designed off-line to approximate the inverse dynamics of the smart mechanism. Through on-line control, the strain crest of the flexible link is reduced 60 percent or so and the dynamic performance of the smart mechanism is improved significantly.
    keyword(s): Linkages , Vibration control , Actuators , Artificial neural networks , Piezoelectric ceramics , Sensors , Strain gages , Adaptive control AND Control equipment ,
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      Neural Networks Based Active Vibration Control of Flexible Linkage Mechanisms

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/125639
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    • Journal of Mechanical Design

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    contributor authorY. M. Song
    contributor authorPostdoctor
    contributor authorC. Zhang
    contributor authorY. Q. Yu
    date accessioned2017-05-09T00:05:33Z
    date available2017-05-09T00:05:33Z
    date copyrightJune, 2001
    date issued2001
    identifier issn1050-0472
    identifier otherJMDEDB-27694#266_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/125639
    description abstractAn investigation is presented into the neural networks based active vibration control of flexible linkage mechanisms. A smart mechanism featuring piezoceramic actuators and strain gauge sensors is designed. A nonlinear adaptive control strategy named Neural Networks based Direct Self-Tuning Control (NNBDSC) is employed to suppress the elastodynamic responses of the smart mechanism. To improve the initial robustness of the NNBDSC, the Dynamic Recurrent Neural Network (DRNN) controllers are designed off-line to approximate the inverse dynamics of the smart mechanism. Through on-line control, the strain crest of the flexible link is reduced 60 percent or so and the dynamic performance of the smart mechanism is improved significantly.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleNeural Networks Based Active Vibration Control of Flexible Linkage Mechanisms
    typeJournal Paper
    journal volume123
    journal issue2
    journal titleJournal of Mechanical Design
    identifier doi10.1115/1.1348269
    journal fristpage266
    journal lastpage271
    identifier eissn1528-9001
    keywordsLinkages
    keywordsVibration control
    keywordsActuators
    keywordsArtificial neural networks
    keywordsPiezoelectric ceramics
    keywordsSensors
    keywordsStrain gages
    keywordsAdaptive control AND Control equipment
    treeJournal of Mechanical Design:;2001:;volume( 123 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
    نرم افزار کتابخانه دیجیتال "دی اسپیس" فارسی شده توسط یابش برای کتابخانه های ایرانی | تماس با یابش
    yabeshDSpacePersian