Overview
- Presents computationally efficient MPC algorithms for processes described by Wiener models
- Provides computational efficiency of MPC as a key issue in this book
- Shows approaches using on-line models or trajectory linearization
Part of the book series: Studies in Systems, Decision and Control (SSDC, volume 389)
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Table of contents (9 chapters)
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Preliminaries
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State-Space Approaches
Keywords
About this book
A linear approximation of the Wiener model or the predicted trajectory is found on-line. As a result, quadratic optimisation tasks are obtained. Furthermore, parameterisation using Laguerre functions is possible to reduce the number of decision variables. Simulation results for ten benchmark processes show that the discussed MPC algorithms lead to excellent control quality. For a neutralisation reactor and a fuel cell, essential advantages ofneural Wiener models are demonstrated.
Reviews
“The present book provides computationally efficient MPC (model predictive control) solutions as an alternative for the classical one, which has a limited structure, giving poor control quality in the case of an imperfect model and disturbances. The book is of real interest for all researchers working in control theory, optimization, engineering and economics.” (Savin Treanta, zbMATH 1510.93001, 2023)
Authors and Affiliations
Bibliographic Information
Book Title: Nonlinear Predictive Control Using Wiener Models
Book Subtitle: Computationally Efficient Approaches for Polynomial and Neural Structures
Authors: Maciej Ławryńczuk
Series Title: Studies in Systems, Decision and Control
DOI: https://doi.org/10.1007/978-3-030-83815-7
Publisher: Springer Cham
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-83814-0Published: 22 September 2021
Softcover ISBN: 978-3-030-83817-1Published: 23 September 2022
eBook ISBN: 978-3-030-83815-7Published: 21 September 2021
Series ISSN: 2198-4182
Series E-ISSN: 2198-4190
Edition Number: 1
Number of Pages: XXIII, 343
Number of Illustrations: 46 b/w illustrations, 121 illustrations in colour