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    Magnetic Bearing Rotordynamic System Optimization Using Multi Objective Genetic Algorithms

    Source: Journal of Dynamic Systems, Measurement, and Control:;2015:;volume( 137 ):;issue: 002::page 21012
    Author:
    Zhong, Wan
    ,
    Palazzolo, Alan
    DOI: 10.1115/1.4028401
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: Multiple objective genetic algorithms (MOGAs) simultaneously optimize a control law and geometrical features of a set of homopolar magnetic bearings (HOMB) supporting a generic flexible, spinning shaft. The minimization objectives include shaft dynamic response (vibration), actuator mass and total actuator power losses. Levitation of the spinning rotor and dynamic stability are constraint conditions for the control law search. Nonlinearities include magnetic flux saturation, and current and voltage limits. Pareto frontiers were applied to identify the bestcompromised solution. Mass and vibration reductions improve with a two control law approach.
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      Magnetic Bearing Rotordynamic System Optimization Using Multi Objective Genetic Algorithms

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    http://yetl.yabesh.ir/yetl1/handle/yetl/157457
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    • Journal of Dynamic Systems, Measurement, and Control

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    contributor authorZhong, Wan
    contributor authorPalazzolo, Alan
    date accessioned2017-05-09T01:16:14Z
    date available2017-05-09T01:16:14Z
    date issued2015
    identifier issn0022-0434
    identifier otherds_137_02_021012.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/157457
    description abstractMultiple objective genetic algorithms (MOGAs) simultaneously optimize a control law and geometrical features of a set of homopolar magnetic bearings (HOMB) supporting a generic flexible, spinning shaft. The minimization objectives include shaft dynamic response (vibration), actuator mass and total actuator power losses. Levitation of the spinning rotor and dynamic stability are constraint conditions for the control law search. Nonlinearities include magnetic flux saturation, and current and voltage limits. Pareto frontiers were applied to identify the bestcompromised solution. Mass and vibration reductions improve with a two control law approach.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleMagnetic Bearing Rotordynamic System Optimization Using Multi Objective Genetic Algorithms
    typeJournal Paper
    journal volume137
    journal issue2
    journal titleJournal of Dynamic Systems, Measurement, and Control
    identifier doi10.1115/1.4028401
    journal fristpage21012
    journal lastpage21012
    identifier eissn1528-9028
    treeJournal of Dynamic Systems, Measurement, and Control:;2015:;volume( 137 ):;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