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    Neural Network–Driven Reentry Reference Trajectory Design and Tracking Using Sliding Mode Control

    Source: Journal of Aerospace Engineering:;2025:;Volume ( 038 ):;issue: 006::page 04025104-1
    Author:
    Mishra, Deepak
    ,
    Sushnigdha, Gangireddy
    DOI: 10.1061/JAEEEZ.ASENG-6130
    Publisher: American Society of Civil Engineers
    Abstract: AbstractThis paper introduces a novel method for designing the optimal reentry trajectory for the hypersonic winged reusable launch vehicle, X-33. The proposed method utilizes a cascaded neural network structure to determine crucial parameters for ...
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      Neural Network–Driven Reentry Reference Trajectory Design and Tracking Using Sliding Mode Control

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    https://yetl.yabesh.ir/yetl1/handle/yetl/4314096
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    contributor authorMishra, Deepak
    contributor authorSushnigdha, Gangireddy
    date accessioned2026-08-20T21:11:50Z
    date available2026-08-20T21:11:50Z
    date copyright2025/09/15
    date issued2025
    identifier otherJAEEEZ.ASENG-6130.pdf
    identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4314096
    description abstractAbstractThis paper introduces a novel method for designing the optimal reentry trajectory for the hypersonic winged reusable launch vehicle, X-33. The proposed method utilizes a cascaded neural network structure to determine crucial parameters for ...
    publisherAmerican Society of Civil Engineers
    titleNeural Network–Driven Reentry Reference Trajectory Design and Tracking Using Sliding Mode Control
    typeJournal Article
    journal volume38
    journal issue6
    journal titleJournal of Aerospace Engineering
    identifier doi10.1061/JAEEEZ.ASENG-6130
    journal fristpage04025104-1
    journal lastpage04025104-12
    page12
    treeJournal of Aerospace Engineering:;2025:;Volume ( 038 ):;issue: 006
    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