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Dynamic Modeling, Predictive Control and Performance Monitoring
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ISBN: 9781848002326

A typical design procedure for model predictive control or control performance monitoring consists of: 1. identification of a parametric or nonparametric model; 2. derivation of the outpu… Plus…

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Dynamic Modeling, Predictive Control and Performance Monitoring: A Data-driven Subspace Approach (Lecture Notes in Control and Information Sciences, Band 374) - Huang, Biao
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Dynamic Modeling, Predictive Control and Performance Monitoring: A Data-driven Subspace Approach (Lecture Notes in Control and Information Sciences, Band 374) - Livres de poche

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Mitwirkende: Kadali, Ramesh, Springer, Taschenbuch, Auflage: 2008, 268 Seiten, Publiziert: 2008-04-11T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 23519108, 0.84 kg, Hardware & Technik… Plus…

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Dynamic Modeling, Predictive Control and Performance Monitoring A Data-driven Subspace Approach 2008 - Huang, Biao und Ramesh Kadali
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Dynamic Modeling Predictive Control and Performance Monitoring - Biao Huang/ Ramesh Kadali
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Dynamic Modeling Predictive Control and Performance Monitoring - Livres de poche

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Dynamic Modeling, Predictive Control and Performance Monitoring : A Data-Driven Subspace Approach by Biao, Kadali, Ramesh Huang - Biao, Kadali, Ramesh Huang
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Dynamic Modeling, Predictive Control and Performance Monitoring : A Data-Driven Subspace Approach by Biao, Kadali, Ramesh Huang - livre d'occasion

ISBN: 9781848002326

The authors provide a "data-driven" approach. No traditional parametric models are used: the intermediate subspace matrices are used directly for the designs. Thus the design process is s… Plus…

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Dynamic Modeling Predictive Control and Performance Monitoring
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Titre:
ISBN:

9781848002326


A typical design procedure for model predictive control or control performance monitoring consists of: 1. identification of a parametric or nonparametric model; 2. derivation of the output predictor from the model; 3. design of the control law or calculation of performance indices according to the predictor.Both design problems need an explicit model form and both require this three-step design procedure. Can this design procedure be simplified? Can an explicit model be avoided? With these questions in mind, the authors eliminate the first and second step of the above design procedure, a "data-driven" approach in the sense that no traditional parametric models are used; hence, the intermediate subspace matrices, which are obtained from the process data and otherwise identified as a first step in the subspace identification methods, are used directly for the designs. Without using an explicit model, the design procedure is simplified and the modelling error caused by parameterization is eliminated.

Informations détaillées sur le livre - Dynamic Modeling Predictive Control and Performance Monitoring


EAN (ISBN-13): 9781848002326
ISBN (ISBN-10): 1848002327
Version reliée
Livre de poche
Date de parution: 2008
Editeur: Springer London
242 Pages
Poids: 0,410 kg
Langue: eng/Englisch

Livre dans la base de données depuis 2008-04-29T14:50:35+02:00 (Paris)
Page de détail modifiée en dernier sur 2024-03-01T12:49:15+01:00 (Paris)
ISBN/EAN: 9781848002326

ISBN - Autres types d'écriture:
1-84800-232-7, 978-1-84800-232-6
Autres types d'écriture et termes associés:
Auteur du livre: huang, schreiber, alexander worth
Titre du livre: information performance, monitor, monitoring, dynamic modeling, lecture performance, model predictive control, driven, data, into the performance, huang, information and control

Données de l'éditeur

Auteur: Biao Huang; Ramesh Kadali
Titre: Lecture Notes in Control and Information Sciences; Dynamic Modeling, Predictive Control and Performance Monitoring - A Data-driven Subspace Approach
Editeur: Springer; Springer London
242 Pages
Date de parution: 2008-04-11
London; GB
Imprimé / Fabriqué en
Langue: Anglais
106,99 € (DE)
109,99 € (AT)
118,00 CHF (CH)
POD
XXIV, 242 p. 63 illus.

BC; Hardcover, Softcover / Technik/Elektronik, Elektrotechnik, Nachrichtentechnik; Regelungstechnik; Verstehen; Benchmarking; Control; Control Engineering; Control Theory; Model Predictive Control; Monitoring; Performance Monitoring; Process Control; Subspace; System Identification; model; modeling; complexity; Control and Systems Theory; Systems Theory, Control; Industrial Chemistry; Multibody Systems and Mechanical Vibrations; Control, Robotics, Automation; Applied Dynamical Systems; Kybernetik und Systemtheorie; Industrielle Chemie und Chemietechnologie; Maschinenbau: Festkörpermechanik; Mathematik für Ingenieure; EA

I Dynamic Modeling through Subspace Identification.- System Identification: Conventional Approach.- Open-loop Subspace Identification.- Closed-loop Subspace Identification.- Identification of Dynamic Matrix and Noise Model Using Closed-loop Data.- II Predictive Control.- Model Predictive Control: Conventional Approach.- Data-driven Subspace Approach to Predictive Control.- III Control Performance Monitoring.- Control Loop Performance Assessment: Conventional Approach.- State-of-the-art MPC Performance Monitoring.- Subspace Approach to MIMO Feedback Control Performance Assessment.- Prediction Error Approach to Feedback Control Performance Assessment.- Performance Assessment with LQG-benchmark from Closed-loop Data.
Provides the reader with control design methods derived directly from process data Simplifies control design and avoids the modelling errors consequent on parameterization
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