System Identification and Adaptive Control

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: System Identification and Adaptive Control
Περιγραφή: Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in:• contemporary power generation;• process control and• conventional benchmarking problems.Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.
Συγγραφείς: Yiannis Boutalis, Dimitrios Theodoridis, Theodore Kottas, Manolis A. Christodoulou
Resource Type: eBook.
Θέματα: Artificial intelligence, Engineering, Adaptive control systems, System identification, System identification--Data processing, Industrial engineering
Categories: TECHNOLOGY & ENGINEERING / Electrical, COMPUTERS / Artificial Intelligence / General, TECHNOLOGY & ENGINEERING / Engineering (General), TECHNOLOGY & ENGINEERING / Industrial Engineering
Βάση Δεδομένων: eBook Index
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RelevancyScore: 912
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PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 912.106750488281
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  Data: Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in:• contemporary power generation;• process control and• conventional benchmarking problems.Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.
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RecordInfo BibRecord:
  BibEntity:
    Classifications:
      – Code: 629.836
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Artificial intelligence
        Type: general
      – SubjectFull: Engineering
        Type: general
      – SubjectFull: Adaptive control systems
        Type: general
      – SubjectFull: System identification
        Type: general
      – SubjectFull: System identification--Data processing
        Type: general
      – SubjectFull: Industrial engineering
        Type: general
    Titles:
      – TitleFull: System Identification and Adaptive Control
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Yiannis Boutalis
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          Name:
            NameFull: Dimitrios Theodoridis
      – PersonEntity:
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            NameFull: Theodore Kottas
      – PersonEntity:
          Name:
            NameFull: Manolis A. Christodoulou
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          Name:
            NameFull: Yiannis Boutalis
      – PersonEntity:
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            NameFull: Dimitrios Theodoridis
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            NameFull: Theodore Kottas
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            NameFull: Manolis A. Christodoulou
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2014
            – D: 21
              M: 05
              Type: profile
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9783319063638
            – Type: isbn-electronic
              Value: 9783319063645
          Titles:
            – TitleFull: System Identification and Adaptive Control
              Type: main
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