Nonlinear Model Predictive Control: Theory and Algorithms by Lars Gr?ne (English

Description: Nonlinear Model Predictive Control by Lars GrÜne, JÜrgen Pannek Nonlinear Model Predictive Control is a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. An introduction to nonlinear optimal control algorithms gives insight into how the nonlinear optimisation routine – the core of any NMPC controller – works. FORMAT Hardcover LANGUAGE English CONDITION Brand New Publisher Description 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 enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. Notes Provides researchers with a self-contained reference for nonlinear model predictive control which can support further researchOffers the student an up-to-date account of nonlinear model predictive control written in a textbook style for easier learningGives the lecturer a sourcebook for teaching nonlinear model predictive control without needing to work up material from papers and contributed booksClassroom tested Back Cover Nonlinear model predictive control (NMPC) is widely used in the process and chemical industries and increasingly for applications, such as those in the automotive industry, which use higher data sampling rates. Nonlinear Model Predictive Control is a thorough and rigorous introduction to 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 Table of Contents Introduction.- Discrete-time and Sampled-data Systems.- Nonlinear Model Predictive Control.- Infinite-horizon Optimal Control.- Stability and Suboptimality Using Stabilizing Constraints.- Stability and Suboptimality without Stabilizing Constraints.- Feasibility and Robustness.- Numerical Discretization.- Numerical Optimal Control of Nonlinear Systems.- Examples.- Appendix: Brief Introduction to NMPC Software. Review "The book provides an excellent and extensive treatment of NMPC from a careful introduction to the underlying theory to advanced results. It can be used for independent reading by applied mathematicians, control theoreticians and engineers who desire a rigorous introduction into the NMPC theory. It can also be used as a textbook for a graduate-level university course in NMPC." (Ilya Kolmanovsky, Mathematical Reviews, April, 2015)"In the monograph nonlinear, discrete-time, finite-dimensional control systems with constant parameters are considered. … Each chapter of the monograph contains many numerical examples which illustrate the theoretical considerations, several possible extensions and open problems. Moreover, relationships to results on predictive control published in the literature are pointed out." (Jerzy Klamka, Zentralblatt MATH, Vol. 1220, 2011) Long Description Nonlinear model predictive control (NMPC) is widely used in the process and chemical industries and increasingly for applications, such as those in the automotive industry, which use higher data sampling rates. Nonlinear Model Predictive Control is a thorough and rigorous introduction to 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 Review Quote From the reviews:In the monograph nonlinear, discrete-time, finite-dimensional control systems with constant parameters are considered. … Each chapter of the monograph contains many numerical examples which illustrate the theoretical considerations, several possible extensions and open problems. Moreover, relationships to results on predictive control published in the literature are pointed out. (Jerzy Klamka, Zentralblatt MATH, Vol. 1220, 2011) Feature Provides researchers with a self-contained reference for nonlinear model predictive control which can support further research Offers the student an up-to-date account of nonlinear model predictive control written in a textbook style for easier learning Gives the lecturer a sourcebook for teaching nonlinear model predictive control without needing to work up material from papers and contributed books Classroom tested Details ISBN0857295004 Short Title NONLINEAR MODEL PREDICTIVE CON Edition Description Edition. Language English ISBN-10 0857295004 ISBN-13 9780857295002 Media Book Format Hardcover Publisher Springer London Ltd Series Communications and Control Engineering Year 2011 Imprint Springer London Ltd Place of Publication England Country of Publication United Kingdom DEWEY 629.836 Subtitle Theory and Algorithms DOI 10.1007/978-0-85729-501-9 Publication Date 2011-04-10 AU Release Date 2011-04-10 NZ Release Date 2011-04-10 UK Release Date 2011-04-10 Author JÜrgen Pannek Pages 360 Alternative 9781447126492 Audience Professional & Vocational Illustrations XII, 360 p. With online files/update. We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:96312741;

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