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Download the fantastic book titled Nonlinear Model Predictive Control written by Lars Grüne, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Nonlinear Model Predictive Control", which was released on 28 June 2018. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Technology & Engineering genre.

Summary of Nonlinear Model Predictive Control by Lars Grüne PDF

This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed, and intuitive examples illustrate the performance of different NMPC variants. 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. An introduction to nonlinear optimal control algorithms yields essential insights into how the nonlinear optimization routine—the core of any nonlinear model predictive controller—works. Accompanying software in MATLAB® and C++ (downloadable from extras.springer.com/), together with an explanatory appendix in the book itself, enables readers to perform computer experiments exploring the possibilities and limitations of NMPC. The second edition has been substantially rewritten, edited and updated to reflect the significant advances that have been made since the publication of its predecessor, including: • a new chapter on economic NMPC relaxing the assumption that the running cost penalizes the distance to a pre-defined equilibrium; • a new chapter on distributed NMPC discussing methods which facilitate the control of large-scale systems by splitting up the optimization into smaller subproblems; • an extended discussion of stability and performance using approximate updates rather than full optimization; • replacement of the pivotal sufficient condition for stability without stabilizing terminal conditions with a weaker alternative and inclusion of an alternative and much simpler proof in the analysis; and • further variations and extensions in response to suggestions from readers of the first edition. Though primarily aimed at academic researchers and practitioners working in control and optimization, the text is self-contained, featuring background material on infinite-horizon optimal control and Lyapunov stability theory that also makes it accessible for graduate students in control engineering and applied mathematics.


Detail About Nonlinear Model Predictive Control PDF

  • Author : Lars Grüne
  • Publisher : Springer
  • Genre : Technology & Engineering
  • Total Pages : 0 pages
  • ISBN : 9783319834238
  • PDF File Size : 19,5 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Nonlinear Model Predictive Control

Nonlinear Model Predictive Control
  • Publisher : Springer
  • File Size : 20,6 Mb
  • Release Date : 28 June 2018
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This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed,

Nonlinear Model Predictive Control

Nonlinear Model Predictive Control
  • Publisher : Springer
  • File Size : 30,8 Mb
  • Release Date : 09 November 2016
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This book offers readers a thorough and rigorous introduction to nonlinear model predictive control (NMPC) for discrete-time and sampled-data systems. NMPC schemes with and without stabilizing terminal constraints are detailed,

Nonlinear Model Predictive Control

Nonlinear Model Predictive Control
  • Publisher : Birkhäuser
  • File Size : 26,5 Mb
  • Release Date : 06 December 2012
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During the past decade model predictive control (MPC), also referred to as receding horizon control or moving horizon control, has become the preferred control strategy for quite a number of

Explicit Nonlinear Model Predictive Control

Explicit Nonlinear Model Predictive Control
  • Publisher : Springer
  • File Size : 33,5 Mb
  • Release Date : 22 March 2012
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Nonlinear Model Predictive Control (NMPC) has become the accepted methodology to solve complex control problems related to process industries. The main motivation behind explicit NMPC is that an explicit state

Model Predictive Control in the Process Industry

Model Predictive Control in the Process Industry
  • Publisher : Springer Science & Business Media
  • File Size : 54,5 Mb
  • Release Date : 06 December 2012
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Model Predictive Control is an important technique used in the process control industries. It has developed considerably in the last few years, because it is the most general way of

Nonlinear Model Predictive Control of Combustion Engines

Nonlinear Model Predictive Control of Combustion Engines
  • Publisher : Springer Nature
  • File Size : 36,8 Mb
  • Release Date : 27 April 2021
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This book provides an overview of the nonlinear model predictive control (NMPC) concept for application to innovative combustion engines. Readers can use this book to become more expert in advanced

Nonlinear Model Predictive Control

Nonlinear Model Predictive Control
  • Publisher : Springer Science & Business Media
  • File Size : 41,5 Mb
  • Release Date : 11 April 2011
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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

Economic Nonlinear Model Predictive Control

Economic Nonlinear Model Predictive Control
  • Publisher : Foundations and Trends in Systems and Control
  • File Size : 35,8 Mb
  • Release Date : 12 January 2018
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In recent years, Economic Model Predictive Control (EMPC) has received considerable attention of many research groups. The present tutorial survey summarizes state-of-the-art approaches in EMPC. In this context EMPC is

Receding Horizon Control

Receding Horizon Control
  • Publisher : Springer Science & Business Media
  • File Size : 31,8 Mb
  • Release Date : 04 October 2005
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Easy-to-follow learning structure makes absorption of advanced material as pain-free as possible Introduces complete theories for stability and cost monotonicity for constrained and non-linear systems as well as for linear

Non-linear Predictive Control

Non-linear Predictive Control
  • Publisher : IET
  • File Size : 48,6 Mb
  • Release Date : 26 October 2001
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The advantage of model predictive control is that it can take systematic account of constraints, thereby allowing processes to operate at the limits of achievable performance. Engineers in academia, industry,