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Titlebook: Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems; A Time/Space Separat Han-Xiong Li,Chenkun Qi Book 2011 Springer Nether

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發(fā)表于 2025-3-21 17:20:23 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems
副標(biāo)題A Time/Space Separat
編輯Han-Xiong Li,Chenkun Qi
視頻videohttp://file.papertrans.cn/874/873611/873611.mp4
概述systematic review of the progress so far on modelling of distributed parameter systems;.unified view from the time/space separation to synthesize to different methods;.some new spatio-temporal models
叢書名稱Intelligent Systems, Control and Automation: Science and Engineering
圖書封面Titlebook: Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems; A Time/Space Separat Han-Xiong Li,Chenkun Qi Book 2011 Springer Nether
描述.The purpose of this volume is to provide a brief review of the previous work on model reduction and identifi cation of distributed parameter systems (DPS), and develop new spatio-temporal models and their relevant identifi cation approaches..In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-oriented nonlinear systems in traditional lumped parameter systems (LPS) is extended to DPS, which results in the spatio-temporal Wiener and Hammerstein systems and their identifi cation methods. Then, the traditional Volterra model is extended to DPS, which results in the spatio-temporal Volterra model and its identification algorithm. All these methods are based on linear time/space separation. Sometimes, the nonlinear time/space separation can play a better role in modeling of very complex processes..Thus, a nonlinear time/space separation based neural modeling is also presented for a class of DPS with more complicated dynamics. Finally, all these modeling approaches are successfully applied to industrial thermal processes, including a cata
出版日期Book 2011
關(guān)鍵詞DPS; DPS; DPS; control; control; control; spatio-temporal modeling; spatio-temporal modeling; spatio-tempora
版次1
doihttps://doi.org/10.1007/978-94-007-0741-2
isbn_softcover978-94-017-8254-8
isbn_ebook978-94-007-0741-2Series ISSN 2213-8986 Series E-ISSN 2213-8994
issn_series 2213-8986
copyrightSpringer Netherlands 2011
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Spatio-Temporal Modeling of Nonlinear Distributed Parameter Systems978-94-007-0741-2Series ISSN 2213-8986 Series E-ISSN 2213-8994
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Intelligent Systems, Control and Automation: Science and Engineeringhttp://image.papertrans.cn/s/image/873611.jpg
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Introduction,This chapter is an introduction of the book. Starting from typical examples of distributed parameter systems (.) encountered in the real-world, it briefly introduces the background and the motivation of the research, and finally the contributions and organization of the book.
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Book 2011(DPS), and develop new spatio-temporal models and their relevant identifi cation approaches..In this book, a systematic overview and classifi cation on the modeling of DPS is presented fi rst, which includes model reduction, parameter estimation and system identifi cation. Next, a class of block-ori
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Spatio-Temporal Volterra Modeling for a Class of Nonlinear DPS,l, the Karhunen-Loève (.) method is used for the time/space separation and dimension reduction. Then the model can be estimated with a least-squares algorithm with the convergence guaranteed under noisy measurements. The simulation and experiment are conducted to demonstrate the effectiveness of the presented modeling method.
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