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Nonlinear Model Predictive Control, Grune


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Цена: 22359.00р.
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Автор: Grune
Название:  Nonlinear Model Predictive Control
Перевод названия: Ларс Грюн: Нелинейная модель интеллектуального управления
ISBN: 9780857295002
Издательство: Springer
Классификация:





ISBN-10: 0857295004
Обложка/Формат: Mixed media product
Страницы: 382
Вес: 0.71 кг.
Дата издания: 01.04.2011
Серия: Communications and Control Engineering
Язык: English
Иллюстрации: 55 black & white illustrations, 9 colour illustrations, 3 black & white tables
Размер: 243 x 162 x 20
Читательская аудитория: Professional & vocational
Подзаголовок: Theory and algorithms
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: 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.


Predictive Control for Linear and Hybrid Systems

Автор: Borrelli
Название: Predictive Control for Linear and Hybrid Systems
ISBN: 1107652871 ISBN-13(EAN): 9781107652873
Издательство: Cambridge Academ
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Цена: 9502.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: With a simple, unified approach, and with consideration of real-time applications, this book covers the theory of stability, feasibility, and robustness of model predictive control (MPC). It is for graduate and postgraduate students, as well as advanced control practitioners interested in the theory and/or implementation of predictive control.

Model Predictive Control

Автор: Camacho
Название: Model Predictive Control
ISBN: 1852336943 ISBN-13(EAN): 9781852336943
Издательство: Springer
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Цена: 9781.00 р.
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Описание: 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.

Nonlinear Model Predictive Control

Автор: Lalo Magni; Davide Martino Raimondo; Frank Allg?we
Название: Nonlinear Model Predictive Control
ISBN: 3642010938 ISBN-13(EAN): 9783642010934
Издательство: Springer
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Цена: 22203.00 р.
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Описание: Over the 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. This book assesses the status of the NMPC field and discusses future directions and needs.

Economic Model Predictive Control

Автор: Ellis
Название: Economic Model Predictive Control
ISBN: 3319411071 ISBN-13(EAN): 9783319411071
Издательство: Springer
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Цена: 19564.00 р.
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Описание: This book presents general methods for the design of economic model predictive control (EMPC) systems for broad classes of nonlinear systems that address key theoretical and practical considerations including recursive feasibility, closed-loop stability, closed-loop performance, and computational efficiency. Specifically, the book proposes:Lyapunov-based EMPC methods for nonlinear systems; two-tier EMPC architectures that are highly computationally efficient; and EMPC schemes handling explicitly uncertainty, time-varying cost functions, time-delays and multiple-time-scale dynamics.The proposed methods employ a variety of tools ranging from nonlinear systems analysis, through Lyapunov-based control techniques to nonlinear dynamic optimization. The applicability and performance of the proposed methods are demonstrated through a number of chemical process examples.The book presents state-of-the-art methods for the design of economic model predictive control systems for chemical processes.In addition to being mathematically rigorous, these methods accommodate key practical issues, for example, direct optimization of process economics, time-varying economic cost functions and computational efficiency. Numerous comments and remarks providing fundamental understanding of the merging of process economics and feedback control into a single framework are included. A control engineer can easily tailor the many detailed examples of industrial relevance given within the text to a specific application.The authors present a rich collection of new research topics and references to significant recent work making Economic Model Predictive Control an important source of information and inspiration for academics and graduate students researching the area and for process engineers interested in applying its ideas.

Predictive Control for Linear and Hybrid Systems

Автор: Borrelli
Название: Predictive Control for Linear and Hybrid Systems
ISBN: 1107016886 ISBN-13(EAN): 9781107016880
Издательство: Cambridge Academ
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Цена: 19800.00 р.
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Описание: Model Predictive Control (MPC), the dominant advanced control approach in industry over the past twenty-five years, is presented comprehensively in this unique book. With a simple, unified approach, and with attention to real-time implementation, it covers predictive control theory including the stability, feasibility, and robustness of MPC controllers. The theory of explicit MPC, where the nonlinear optimal feedback controller can be calculated efficiently, is presented in the context of linear systems with linear constraints, switched linear systems, and, more generally, linear hybrid systems. Drawing upon years of practical experience and using numerous examples and illustrative applications, the authors discuss the techniques required to design predictive control laws, including algorithms for polyhedral manipulations, mathematical and multiparametric programming and how to validate the theoretical properties and to implement predictive control policies. The most important algorithms feature in an accompanying free online MATLAB toolbox, which allows easy access to sample solutions. Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.

Predictive Analytics for Dummies

Автор: Bari Anasse, Chaouchi Mohamed, Jung Tommy
Название: Predictive Analytics for Dummies
ISBN: 1119267005 ISBN-13(EAN): 9781119267003
Издательство: Wiley
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Цена: 4117.00 р.
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Описание: Use Big Data and technology to uncover real-world insights You don`t need a time machine to predict the future. All it takes is a little knowledge and know-how, and Predictive Analytics For Dummies gets you there fast.

Nonlinear dynamical systems and control

Автор: Haddad, Wassim M. Chellaboina, Vijaysekhar
Название: Nonlinear dynamical systems and control
ISBN: 0691133298 ISBN-13(EAN): 9780691133294
Издательство: Wiley
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Цена: 23760.00 р.
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Описание: Presents and develops an extensive treatment of stability analysis and control design of nonlinear dynamical systems, with an emphasis on Lyapunov-based methods. This graduate-level textbook is suitable for applied mathematicians, dynamical systems theorists, control theorists, and engineers.

Machine Learning Control – Taming Nonlinear Dynamics and Turbulence

Автор: Duriez
Название: Machine Learning Control – Taming Nonlinear Dynamics and Turbulence
ISBN: 331940623X ISBN-13(EAN): 9783319406237
Издательство: Springer
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Цена: 10760.00 р.
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Описание: This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. In Chapter 5, MLC detects and exploits a strongly nonlinear actuation mechanism of a low-dimensional dynamical system when linear control methods are shown to fail.


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