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Published by Springer International Publishing, 2016
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Published by Springer London Ltd, England, 2011
ISBN 10: 0857295004 ISBN 13: 9780857295002
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Hardcover. Condition: new. Hardcover. 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Add to basketPaperback. Condition: Brand New. 2nd reprint edition. 456 pages. 9.25x6.10x1.07 inches. In Stock.
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Add to basketHardcover. Condition: Brand New. har/psc edition. 359 pages. 9.75x6.50x0.75 inches. In Stock.
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ISBN 10: 0857295004 ISBN 13: 9780857295002
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Add to basketHardcover. Condition: new. Hardcover. 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 lea.
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