Description: Nonlinear Model Predictive Control Please note: this item is printed on demand and will take extra time before it can be dispatched to you (up to 20 working days). Theory and Algorithms Author(s): Lars Gr?ne, J?rgen Pannek Format: Hardback Publisher: Springer London Ltd, United Kingdom Imprint: Springer London Ltd ISBN-13: 9780857295002, 978-0857295002 Synopsis Nonlinear Model Predictive Control is a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC is interpreted as an approximation of infinite-horizon optimal control so that important properties like closed-loop stability, inverse optimality and suboptimality can be derived in a uniform manner. These results are complemented by discussions of feasibility and robustness. NMPC schemes with and without stabilizing terminal constraints are detailed and intuitive examples illustrate the performance of different NMPC variants. An introduction to nonlinear optimal control algorithms gives insight into how the nonlinear optimisation routine ? the core of any NMPC controller ? works. An appendix covering NMPC software and accompanying software in MATLAB? and C++(downloadable from [url] enables readers to perform computer experiments exploring the possibilities and limitations of NMPC.
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Book Title: Nonlinear Model Predictive Control
Number of Pages: 360 Pages
Language: English
Publication Name: Nonlinear Model Predictive Control: Theory and Algorithms
Publisher: Springer London LTD
Publication Year: 2011
Subject: Engineering & Technology, Computer Science, Mechanics
Item Height: 235 mm
Item Weight: 723 g
Type: Textbook
Author: Lars Grune, Jurgen Pannek
Subject Area: Mechanical Engineering, Chemical Engineering
Series: Communications and Control Engineering
Item Width: 155 mm
Format: Hardcover
