Model Predictive Control
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Model Predictive Control
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Author : Eduardo F. Camacho
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-01-10
Model Predictive Control written by Eduardo F. Camacho and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-10 with Technology & Engineering categories.
The second edition of "Model Predictive Control" provides a thorough introduction to theoretical and practical aspects of the most commonly used MPC strategies. It bridges the gap between the powerful but often abstract techniques of control researchers and the more empirical approach of practitioners. The book demonstrates that a powerful technique does not always require complex control algorithms. Many new exercises and examples have also been added throughout. Solutions available for download from the authors' website save the tutor time and enable the student to follow results more closely even when the tutor isn't present.
Nonlinear Model Predictive Control
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Author : Lars Grüne
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-04-11
Nonlinear Model Predictive Control written by Lars Grüne and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-11 with Technology & Engineering categories.
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 www.springer.com/ISBN) enables readers to perform computer experiments exploring the possibilities and limitations of NMPC.
Model Predictive Control
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Author : Basil Kouvaritakis
language : en
Publisher: Springer
Release Date : 2015-12-01
Model Predictive Control written by Basil Kouvaritakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-01 with Technology & Engineering categories.
For the first time, a textbook that brings together classical predictive control with treatment of up-to-date robust and stochastic techniques. Model Predictive Control describes the development of tractable algorithms for uncertain, stochastic, constrained systems. The starting point is classical predictive control and the appropriate formulation of performance objectives and constraints to provide guarantees of closed-loop stability and performance. Moving on to robust predictive control, the text explains how similar guarantees may be obtained for cases in which the model describing the system dynamics is subject to additive disturbances and parametric uncertainties. Open- and closed-loop optimization are considered and the state of the art in computationally tractable methods based on uncertainty tubes presented for systems with additive model uncertainty. Finally, the tube framework is also applied to model predictive control problems involving hard or probabilistic constraints for the cases of multiplicative and stochastic model uncertainty. The book provides: extensive use of illustrative examples; sample problems; and discussion of novel control applications such as resource allocation for sustainable development and turbine-blade control for maximized power capture with simultaneously reduced risk of turbulence-induced damage. Graduate students pursuing courses in model predictive control or more generally in advanced or process control and senior undergraduates in need of a specialized treatment will find Model Predictive Control an invaluable guide to the state of the art in this important subject. For the instructor it provides an authoritative resource for the construction of courses.
Recent Advances In Model Predictive Control
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Author : Timm Faulwasser
language : en
Publisher: Springer Nature
Release Date : 2021-04-17
Recent Advances In Model Predictive Control written by Timm Faulwasser and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-17 with Science categories.
This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role. The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders.
Model Predictive Control Theory And Applications
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Author : Constantin Voloşencu
language : en
Publisher: BoD – Books on Demand
Release Date : 2023-07-12
Model Predictive Control Theory And Applications written by Constantin Voloşencu and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-12 with Science categories.
The book presents some recent specialized theoretical and practical works in the field of process control based on the model predictive control (MPC) method. It includes seven chapters that present studies on the application of MPC in various technical processes, such as the atmospheric plasma spray process, permanent magnet synchronous motors, monitoring of the pose of a walking person, monitoring of the heat treatment process of raw materials, discrete event processes, control of passenger vehicles, and natural gas sweetening processes. Chapters include examples and case studies from researchers in the field. This volume provides readers with new solutions and answers to questions related to the emerging applications of MPC and their implementation.
Model Predictive Control
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Author : Corrine Wade
language : en
Publisher:
Release Date : 2015
Model Predictive Control written by Corrine Wade and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Predictive control categories.
Although industrial processes are inherently nonlinear, many contributions for controller design for those plants are based on the assumption of a linear model of the system. However, in some cases it is difficult to represent a given process using a linear model. Model Predictive Control (MPC) is an optimal control approach which can effectively deal with constraints and multivariable processes in industries. Because of its advantages, MPC has been widely applied in automotive and process control communities. This book discusses the theory, practices and future challenges of model predictive control.
Model Predictive Control
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Author : James Blake Rawlings
language : en
Publisher:
Release Date : 2017
Model Predictive Control written by James Blake Rawlings and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with Control theory categories.
Nonlinear Model Predictive Control
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Author : Lalo Magni
language : en
Publisher: Springer
Release Date : 2009-05-18
Nonlinear Model Predictive Control written by Lalo Magni and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-05-18 with Technology & Engineering categories.
Over the past few years significant progress has been achieved in the field of nonlinear model predictive control (NMPC), also referred to as receding horizon control or moving horizon control. More than 250 papers have been published in 2006 in ISI Journals. With this book we want to bring together the contributions of a diverse group of internationally well recognized researchers and industrial practitioners, to critically assess the current status of the NMPC field and to discuss future directions and needs. The book consists of selected papers presented at the International Workshop on Assessment an Future Directions of Nonlinear Model Predictive Control that took place from September 5 to 9, 2008, in Pavia, Italy.
Advanced Model Predictive Control
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Author : Tao Zheng
language : en
Publisher: BoD – Books on Demand
Release Date : 2011-07-05
Advanced Model Predictive Control written by Tao Zheng and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-07-05 with Technology & Engineering categories.
Model Predictive Control (MPC) refers to a class of control algorithms in which a dynamic process model is used to predict and optimize process performance. From lower request of modeling accuracy and robustness to complicated process plants, MPC has been widely accepted in many practical fields. As the guide for researchers and engineers all over the world concerned with the latest developments of MPC, the purpose of "Advanced Model Predictive Control" is to show the readers the recent achievements in this area. The first part of this exciting book will help you comprehend the frontiers in theoretical research of MPC, such as Fast MPC, Nonlinear MPC, Distributed MPC, Multi-Dimensional MPC and Fuzzy-Neural MPC. In the second part, several excellent applications of MPC in modern industry are proposed and efficient commercial software for MPC is introduced. Because of its special industrial origin, we believe that MPC will remain energetic in the future.
Nonlinear Model Predictive Control
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Author : Frank Allgöwer
language : en
Publisher: Birkhäuser
Release Date : 2012-11-05
Nonlinear Model Predictive Control written by Frank Allgöwer and has been published by Birkhäuser this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-11-05 with Mathematics categories.
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 industrial processes. There have been many significant advances in this area over the past years, one of the most important ones being its extension to nonlinear systems. This book gives an up-to-date assessment of the current state of the art in the new field of nonlinear model predictive control (NMPC). The main topic areas that appear to be of central importance for NMPC are covered, namely receding horizon control theory, modeling for NMPC, computational aspects of on-line optimization and application issues. The book consists of selected papers presented at the International Symposium on Nonlinear Model Predictive Control – Assessment and Future Directions, which took place from June 3 to 5, 1998, in Ascona, Switzerland. The book is geared towards researchers and practitioners in the area of control engineering and control theory. It is also suited for postgraduate students as the book contains several overview articles that give a tutorial introduction into the various aspects of nonlinear model predictive control, including systems theory, computations, modeling and applications.