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 : Frank Allgöwer
language : en
Publisher: Birkhäuser
Release Date : 2012-12-06
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 2012-12-06 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.
Predictive Control
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Author : Ronald Soeterboek
language : en
Publisher: Prentice Hall International
Release Date : 1992
Predictive Control written by Ronald Soeterboek and has been published by Prentice Hall International this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with Technology & Engineering categories.
Describes in detail how several well-known predictive control schemes (for example, DMC and GPC) and other, more formal controller design methods can be formulated within a unified framework. The influence of the design parameters on control system performance and robustness is emphasized.
Predictive Control
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Author : Jan Marian Maciejowski
language : en
Publisher: Pearson Education
Release Date : 2002
Predictive Control written by Jan Marian Maciejowski and has been published by Pearson Education this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Psychology categories.
Model predictive control is an indispensable part of industrial control engineering and is increasingly the "method of choice" for advanced control applications. Jan Maciejowski's book provides a systematic and comprehensive course on predictive control suitable for final year students and professional engineers. The first book to cover constrained predictive control, the text reflects the true use of the topic in industry.
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.
Applied Predictive Control
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Author : Sunan Huang
language : en
Publisher: Springer Science & Business Media
Release Date : 2001-11-28
Applied Predictive Control written by Sunan Huang 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 2001-11-28 with Mathematics categories.
This focused treatment includes the fundamentals and some state-of-the-art developments in the field of predictive control. A substantial part of the book addresses application issues in predictive control, providing several interesting case studies for more application-oriented readers.
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.
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 Of Wind Energy Conversion Systems
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Author : Venkata Yaramasu
language : en
Publisher: John Wiley & Sons
Release Date : 2016-12-19
Model Predictive Control Of Wind Energy Conversion Systems written by Venkata Yaramasu and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-19 with Science categories.
Model Predictive Control of Wind Energy Conversion Systems addresses the predicative control strategy that has emerged as a promising digital control tool within the field of power electronics, variable-speed motor drives, and energy conversion systems. The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS. Furthermore, this book: Analyzes a wide variety of practical WECS, illustrating important concepts with case studies, simulations, and experimental results Provides a step-by-step design procedure for the development of predictive control schemes for various WECS configurations Describes continuous- and discrete-time modeling of wind generators and power converters, weighting factor selection, discretization methods, and extrapolation techniques Presents useful material for other power electronic applications such as variable-speed motor drives, power quality conditioners, electric vehicles, photovoltaic energy systems, distributed generation, and high-voltage direct current transmission. Explores S-Function Builder programming in MATLAB environment to implement various MPC strategies through the companion website Reflecting the latest technologies in the field, Model Predictive Control of Wind Energy Conversion Systems is a valuable reference for academic researchers, practicing engineers, and other professionals. It can also be used as a textbook for graduate-level and advanced undergraduate courses.
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.