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    Nonlinear Model Predictive Control of a Laboratory Gas Turbine Installation

    Source: Journal of Engineering for Gas Turbines and Power:;1999:;volume( 121 ):;issue: 004::page 629
    Author:
    B. G. Vroemen
    ,
    H. A. van Essen
    ,
    A. A. van Steenhoven
    ,
    J. J. Kok
    DOI: 10.1115/1.2818518
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: The feasibility of model predictive control (MPC) applied to a laboratory gas turbine installation is investigated. MPC explicitly incorporates (input and output) constraints in its optimizations, which explains the choice for this computationally demanding control strategy. Strong nonlinearities, displayed by the gas turbine installation, cannot always be handled adequately by standard linear MPC. Therefore, we resort to nonlinear methods, based on successive linearization and nonlinear prediction as well as the combination of these. We implement these methods, using a nonlinear model of the installation, and compare them to linear MPC. It is shown that controller performance can be improved, without increasing controller execution-time excessively.
    keyword(s): Gas turbines , Predictive control AND Control equipment ,
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      Nonlinear Model Predictive Control of a Laboratory Gas Turbine Installation

    URI
    https://yetl.yabesh.ir/yetl1/handle/yetl/122086
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    • Journal of Engineering for Gas Turbines and Power

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    contributor authorB. G. Vroemen
    contributor authorH. A. van Essen
    contributor authorA. A. van Steenhoven
    contributor authorJ. J. Kok
    date accessioned2017-05-08T23:59:30Z
    date available2017-05-08T23:59:30Z
    date copyrightOctober, 1999
    date issued1999
    identifier issn1528-8919
    identifier otherJETPEZ-26792#629_1.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/122086
    description abstractThe feasibility of model predictive control (MPC) applied to a laboratory gas turbine installation is investigated. MPC explicitly incorporates (input and output) constraints in its optimizations, which explains the choice for this computationally demanding control strategy. Strong nonlinearities, displayed by the gas turbine installation, cannot always be handled adequately by standard linear MPC. Therefore, we resort to nonlinear methods, based on successive linearization and nonlinear prediction as well as the combination of these. We implement these methods, using a nonlinear model of the installation, and compare them to linear MPC. It is shown that controller performance can be improved, without increasing controller execution-time excessively.
    publisherThe American Society of Mechanical Engineers (ASME)
    titleNonlinear Model Predictive Control of a Laboratory Gas Turbine Installation
    typeJournal Paper
    journal volume121
    journal issue4
    journal titleJournal of Engineering for Gas Turbines and Power
    identifier doi10.1115/1.2818518
    journal fristpage629
    journal lastpage634
    identifier eissn0742-4795
    keywordsGas turbines
    keywordsPredictive control AND Control equipment
    treeJournal of Engineering for Gas Turbines and Power:;1999:;volume( 121 ):;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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