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Data Driven Strategies : Theory and Applications

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Title: Data Driven Strategies : Theory and Applications
Description: A key challenge in science and engineering is to provide a quantitative description of the systems under investigation, leveraging the noisy data collected. Such a description may be a complete mathematical model or a mechanism to return controllers corresponding to new, unseen inputs. Recent advances in the theories are described in detail, along with their applications in engineering. The book aims to develop model-free system analysis and control strategies, i.e., data-driven control from theoretical analysis and engineering applications based only on measured data. The study aims to develop system identification, and combination in advanced control theory, i.e., data-driven control strategy as system and controller are generated from measured data directly. The book reviews the development of system identification and its combination in advanced control theory, i.e., data-driven control strategy, as they all depend on measured data. Firstly, data-driven identification is developed for the closed-loop, nonlinear system and model validation, i.e., obtaining model descriptions from measured data. Secondly, the data-driven idea is combined with some control strategies to be considered data-driven control strategies, such as data-driven model predictive control, data-driven iterative tuning control, and data-driven subspace predictive control. Thirdly data-driven identification and data-driven control strategies are applied to interested engineering. In this context, the book provides algorithms to perform state estimation of dynamical systems from noisy data and some convex optimization algorithms through identification and control problems.
Authors: Wang Jianhong, Ricardo A. Ramirez-Mendoza, Ruben Morales-Menendez
Resource Type: eBook.
Subjects: System design--Data processing, Automatic control--Data processing, Systems engineering--Data processing
Categories: MATHEMATICS / Optimization
Database: eBook Index
FullText Text:
  Availability: 0
Header DbId: edsebk
DbLabel: eBook Index
An: 3558620
RelevancyScore: 969
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 968.509704589844
IllustrationInfo
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  Data: Data Driven Strategies : Theory and Applications
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  Data: A key challenge in science and engineering is to provide a quantitative description of the systems under investigation, leveraging the noisy data collected. Such a description may be a complete mathematical model or a mechanism to return controllers corresponding to new, unseen inputs. Recent advances in the theories are described in detail, along with their applications in engineering. The book aims to develop model-free system analysis and control strategies, i.e., data-driven control from theoretical analysis and engineering applications based only on measured data. The study aims to develop system identification, and combination in advanced control theory, i.e., data-driven control strategy as system and controller are generated from measured data directly. The book reviews the development of system identification and its combination in advanced control theory, i.e., data-driven control strategy, as they all depend on measured data. Firstly, data-driven identification is developed for the closed-loop, nonlinear system and model validation, i.e., obtaining model descriptions from measured data. Secondly, the data-driven idea is combined with some control strategies to be considered data-driven control strategies, such as data-driven model predictive control, data-driven iterative tuning control, and data-driven subspace predictive control. Thirdly data-driven identification and data-driven control strategies are applied to interested engineering. In this context, the book provides algorithms to perform state estimation of dynamical systems from noisy data and some convex optimization algorithms through identification and control problems.
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  Data: <searchLink fieldCode="AR" term="%22Wang+Jianhong%22">Wang Jianhong</searchLink><br /><searchLink fieldCode="AR" term="%22Ricardo+A%2E+Ramirez-Mendoza%22">Ricardo A. Ramirez-Mendoza</searchLink><br /><searchLink fieldCode="AR" term="%22Ruben+Morales-Menendez%22">Ruben Morales-Menendez</searchLink>
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PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=3558620
RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 629.8
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: System design--Data processing
        Type: general
      – SubjectFull: Automatic control--Data processing
        Type: general
      – SubjectFull: Systems engineering--Data processing
        Type: general
    Titles:
      – TitleFull: Data Driven Strategies : Theory and Applications
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Wang Jianhong
      – PersonEntity:
          Name:
            NameFull: Ricardo A. Ramirez-Mendoza
      – PersonEntity:
          Name:
            NameFull: Ruben Morales-Menendez
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            NameFull: Wang Jianhong
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          Name:
            NameFull: Ricardo A. Ramirez-Mendoza
      – PersonEntity:
          Name:
            NameFull: Ruben Morales-Menendez
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2023
            – D: 01
              M: 04
              Type: profile
              Y: 2023
          Identifiers:
            – Type: isbn-print
              Value: 9780367746599
            – Type: isbn-print
              Value: 9780367750084
            – Type: isbn-electronic
              Value: 9781000860276
            – Type: isbn-electronic
              Value: 9781000860290
            – Type: isbn-electronic
              Value: 9781003160700
          Titles:
            – TitleFull: Data Driven Strategies : Theory and Applications
              Type: main
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