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    Feedforward Feedback Linearization Linear Quadratic Gaussian With Loop Transfer Recovery Control of Piezoelectric Actuator in Active Vibration Isolation System

    Source: Journal of Vibration and Acoustics:;2018:;volume( 140 ):;issue: 004::page 41009
    Author:
    Wang, Shuai
    ,
    Chen, Zhaobo
    ,
    Liu, Xiaoxiang
    ,
    Jiao, Yinghou
    DOI: 10.1115/1.4039245
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Hysteresis exists widely in intelligent materials, such as piezoelectric and giant magnetostrictive ones, and it significantly affects the precision of vibration control when a controlled object moves at a range of micrometers or even smaller. Many measures must be implemented to eliminate the influence of hysteresis. In this work, the hysteresis characteristic of a proposed piezoelectric actuator (PEA) is tested and modeled based on the adaptive neuro fuzzy inference system (ANFIS). A linearization control method with feedforward hysteresis compensation and proportional–integral–derivative (PID) feedback is established and simulated. A linear quadratic Gaussian with loop transfer recovery (LQG/LTR) regulator is then designed as a vibration controller. Verification experiments are conducted to evaluate the effectiveness of the control method in vibration isolation. Experiment results demonstrate that the proposed vibration control system with a feedforward feedback linearization controller and an LQG/LTR regulator can significantly improve the performance of a vibration isolation system in the frequency range of 5–200 Hz with low energy consumption.
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      Feedforward Feedback Linearization Linear Quadratic Gaussian With Loop Transfer Recovery Control of Piezoelectric Actuator in Active Vibration Isolation System

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    contributor authorWang, Shuai
    contributor authorChen, Zhaobo
    contributor authorLiu, Xiaoxiang
    contributor authorJiao, Yinghou
    date accessioned2019-02-28T11:10:39Z
    date available2019-02-28T11:10:39Z
    date copyright2/23/2018 12:00:00 AM
    date issued2018
    identifier issn1048-9002
    identifier othervib_140_04_041009.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4253499
    description abstractHysteresis exists widely in intelligent materials, such as piezoelectric and giant magnetostrictive ones, and it significantly affects the precision of vibration control when a controlled object moves at a range of micrometers or even smaller. Many measures must be implemented to eliminate the influence of hysteresis. In this work, the hysteresis characteristic of a proposed piezoelectric actuator (PEA) is tested and modeled based on the adaptive neuro fuzzy inference system (ANFIS). A linearization control method with feedforward hysteresis compensation and proportional–integral–derivative (PID) feedback is established and simulated. A linear quadratic Gaussian with loop transfer recovery (LQG/LTR) regulator is then designed as a vibration controller. Verification experiments are conducted to evaluate the effectiveness of the control method in vibration isolation. Experiment results demonstrate that the proposed vibration control system with a feedforward feedback linearization controller and an LQG/LTR regulator can significantly improve the performance of a vibration isolation system in the frequency range of 5–200 Hz with low energy consumption.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleFeedforward Feedback Linearization Linear Quadratic Gaussian With Loop Transfer Recovery Control of Piezoelectric Actuator in Active Vibration Isolation System
    typeJournal Paper
    journal volume140
    journal issue4
    journal titleJournal of Vibration and Acoustics
    identifier doi10.1115/1.4039245
    journal fristpage41009
    journal lastpage041009-10
    treeJournal of Vibration and Acoustics:;2018:;volume( 140 ):;issue: 004
    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
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