Computationally Efficient Model Predictive Control Algorithms: A Neural Network Approach - Couverture souple

Ławryńczuk, Maciej

9783319350219: Computationally Efficient Model Predictive Control Algorithms: A Neural Network Approach

Couverture souple

ISBN 10 : 3319350218 ISBN 13 : 9783319350219

Editeur : Springer, 2016

Afficher les exemplaires de cette �dition comportant l?ISBN

1 D'occasion

De EUR 188,57

8 Neuf

De EUR 92,27

This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include:

� A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction.

� Implementation details of the MPC algorithms for feed forward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models.

� The MPC algorithms based on neural multi-models (inspired by the idea of predictive control).

� The MPC algorithms with neural approximation with no on-line linearization.

� The MPC algorithms with guaranteed stability and robustness.

� Cooperation between the MPC algorithms and set-point optimization.

Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require demanding on-line nonlinear optimization. The presented simulation results demonstrate high accuracy and computational efficiency of the algorithms. For a few representative nonlinear benchmark processes, such as chemical reactors and a distillation column, for which the classical MPC algorithms based on linear models do not work properly, the trajectories obtained in the suboptimal MPC algorithms are very similar to those given by the ``ideal'' MPC algorithm with on-line nonlinear optimization repeated at each sampling instant. At the same time, the suboptimal MPC algorithms are significantly less computationally demanding.

Les informations fournies dans la section � Synopsis � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteur: Springer
Date d'�dition: 2016
Langue: anglais
ISBN 10: 3319350218
ISBN 13: 9783319350219
Reliure: Broch�
Nombre de pages: 340
Coordonn�es du fabricant: non disponible

Acheter D'occasion

�tat : Comme neuf

Like New

Afficher cet article

EUR 188,57

Autre devise

EUR 28,97 exp�dition depuis Royaume-Uni vers France

Destinations, frais et d�lais

Ajouter au panier

Acheter neuf

Afficher cet article

EUR 92,27

Autre devise

EUR 9,70 exp�dition depuis Allemagne vers France

Destinations, frais et d�lais

Ajouter au panier

Autres �ditions populaires du m�me titre

9783319042282: Computationally Efficient Model Predictive Control Algorithms

Edition pr�sent�e

ISBN 10 : 3319042289 ISBN 13 : 9783319042282
Editeur : Springer, 2014
Couverture rigide

Springer, 2014 (Couverture souple)

R�sultats de recherche pour Computationally Efficient Model Predictive Control...

Image fournie par le vendeur

Computationally Efficient Model Predictive Control Algorithms

Maciej Lawrynczuk

Edit� par Springer International Publishing, 2016

ISBN 10 : 3319350218 ISBN 13 : 9783319350219

Neuf Couverture souple

impression � la demande

Vendeur : moluna, Greven, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents recent research in Computationally Efficient Model Predictive Control AlgorithmsFocuses on a Neural Network Approach for Model Predictive ControlWritten by an expert in the fieldThis book thoroughly discusses computation. N� de r�f. du vendeur 385703816

Contacter le vendeur

Acheter neuf

EUR 92,27

Autre devise

Frais de port : EUR 9,70

De Allemagne vers France

Destinations, frais et d�lais

Quantit� disponible : Plus de 20 disponibles

Ajouter au panier

Image fournie par le vendeur

Computationally Efficient Model Predictive Control Algorithms : A Neural Network Approach

Maciej �Awry�Czuk

Edit� par Springer International Publishing, 2016

ISBN 10 : 3319350218 ISBN 13 : 9783319350219

Neuf Taschenbuch

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. Implementation details of the MPC algorithms for feed forward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). The MPC algorithms with neural approximation with no on-line linearization. The MPC algorithms with guaranteed stability and robustness. Cooperation between the MPC algorithms and set-point optimization.Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require demanding on-line nonlinear optimization. The presented simulation results demonstrate high accuracy and computational efficiency of the algorithms. For a few representative nonlinear benchmark processes, such as chemical reactors and a distillation column, for which the classical MPC algorithms based on linear models do not work properly, the trajectories obtained in the suboptimal MPC algorithms are very similar to those given by the ``ideal'' MPC algorithm with on-line nonlinear optimization repeated at each sampling instant. At the same time, the suboptimal MPC algorithms are significantly less computationally demanding. N� de r�f. du vendeur 9783319350219

Contacter le vendeur

Acheter neuf

EUR 106,99

Autre devise

Frais de port : EUR 10,99

De Allemagne vers France

Destinations, frais et d�lais

Quantit� disponible : 1 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Computationally Efficient Model Predictive Control Algorithms

Maciej �Awry�Czuk

Edit� par Springer International Publishing Aug 2016, 2016

ISBN 10 : 3319350218 ISBN 13 : 9783319350219

Neuf Taschenbuch

impression � la demande

Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. Implementation details of the MPC algorithms for feed forward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). The MPC algorithms with neural approximation with no on-line linearization. The MPC algorithms with guaranteed stability and robustness. Cooperation between the MPC algorithms and set-point optimization.Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require demanding on-line nonlinear optimization. The presented simulation results demonstrate high accuracy and computational efficiency of the algorithms. For a few representative nonlinear benchmark processes, such as chemical reactors and a distillation column, for which the classical MPC algorithms based on linear models do not work properly, the trajectories obtained in the suboptimal MPC algorithms are very similar to those given by the ``ideal'' MPC algorithm with on-line nonlinear optimization repeated at each sampling instant. At the same time, the suboptimal MPC algorithms are significantly less computationally demanding. 340 pp. Englisch. N� de r�f. du vendeur 9783319350219

Contacter le vendeur

Acheter neuf

EUR 106,99

Autre devise

Frais de port : EUR 11

De Allemagne vers France

Destinations, frais et d�lais

Quantit� disponible : 2 disponible(s)

Ajouter au panier

Image fournie par le vendeur

Computationally Efficient Model Predictive Control Algorithms

Maciej �Awry�Czuk

Edit� par Springer International Publishing, Springer International Publishing Aug 2016, 2016

ISBN 10 : 3319350218 ISBN 13 : 9783319350219

Neuf Taschenbuch

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

�valuation du vendeur 5 sur 5 �toiles

Taschenbuch. Etat : Neu. Neuware -This book thoroughly discusses computationally efficient (suboptimal) Model Predictive Control (MPC) techniques based on neural models. The subjects treated include: A few types of suboptimal MPC algorithms in which a linear approximation of the model or of the predicted trajectory is successively calculated on-line and used for prediction. Implementation details of the MPC algorithms for feed forward perceptron neural models, neural Hammerstein models, neural Wiener models and state-space neural models. The MPC algorithms based on neural multi-models (inspired by the idea of predictive control). The MPC algorithms with neural approximation with no on-line linearization. The MPC algorithms with guaranteed stability and robustness. Cooperation between the MPC algorithms and set-point optimization.Thanks to linearization (or neural approximation), the presented suboptimal algorithms do not require demanding on-line nonlinear optimization. The presented simulation results demonstrate high accuracy and computational efficiency of the algorithms. For a few representative nonlinear benchmark processes, such as chemical reactors and a distillation column, for which the classical MPC algorithms based on linear models do not work properly, the trajectories obtained in the suboptimal MPC algorithms are very similar to those given by the ``ideal'' MPC algorithm with on-line nonlinear optimization repeated at each sampling instant. At the same time, the suboptimal MPC algorithms are significantly less computationally demanding.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 340 pp. Englisch. N� de r�f. du vendeur 9783319350219

Contacter le vendeur