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

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Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

27.08.2016

Abbildungen

XXIV, 316 p. 87 illus.

Verlag

Springer

Seitenzahl

316

Maße (L/B/H)

23,5/15,5/1,9 cm

Gewicht

517 g

Auflage

Softcover reprint of the original 1st ed. 2014

Sprache

Englisch

ISBN

978-3-319-35021-9

Beschreibung

Rezension

“The book represents a good read for those wishing to study and implement Model Predictive Control (MPC) algorithms based on neural network type models. … The presentation of the material in the book is pedagogical and includes the ‘prototype’ nonlinear MPC problem, which is seen as an ‘ideal’ for suboptimal schemes issues from the linearization-based approaches.” (Sorin Olaru, Mathematical Reviews, April, 2017)




“This is a monographic work that reflects a large experience in the exploitation of neural network scenarios for Model Predictive Control (MPC). The book providesa rigorous and self-contained material for some key theoretical topics, accompanied by the description of the associated algorithms. … The exposition is suitable for graduate studies or specialized research stages and requires a medium level of training in control systems engineering.” (Octavian Pastravanu, zbMATH 1330.93002, 2016)

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

27.08.2016

Abbildungen

XXIV, 316 p. 87 illus.

Verlag

Springer

Seitenzahl

316

Maße (L/B/H)

23,5/15,5/1,9 cm

Gewicht

517 g

Auflage

Softcover reprint of the original 1st ed. 2014

Sprache

Englisch

ISBN

978-3-319-35021-9

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

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  • Produktbild: Computationally Efficient Model Predictive Control Algorithms
  • MPC Algorithms.- MPC Algorithms Based on Double-Layer PerceptronNeural Models: the Prototypes.- MPC Algorithms Based on Neural Hammerstein andWiener Models.- MPC Algorithms Based on Neural State-Space Models.- MPC Algorithms Based on Neural Multi-Models.- MPC Algorithms with Neural Approximation.- Stability and Robustness of MPC Algorithms.- Cooperation Between MPC Algorithms and Set-PointOptimisation Algorithms.