Hybrid Predictive Control for Dynamic Transport Problems, Alfredo Nunez; Doris Saez; Cristi?n E. Cort?s
Автор: Borrelli Название: Predictive Control for Linear and Hybrid Systems ISBN: 1107652871 ISBN-13(EAN): 9781107652873 Издательство: Cambridge Academ Рейтинг: 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.
Автор: Sunan Huang; Tong Heng Lee Название: Applied Predictive Control ISBN: 1852333383 ISBN-13(EAN): 9781852333386 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Addresses three main schemes for advanced predictive control: Smith predictive control, generalised predictive control, and a form of predictive control based on finite spectrum assignment. This book addresses application issues in predictive control, providing case studies for application-oriented readers.
Автор: Ellis Название: Economic Model Predictive Control ISBN: 3319411071 ISBN-13(EAN): 9783319411071 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
The book discusses the emerging topic of comprehensive energy management in electric vehicles from the viewpoint of academia and from the industrial perspective. It provides a seamless coverage of all relevant systems and control algorithms for comprehensive energy management, their integration on a multi-core system and their reliability assurance (validation and test). Relevant European projects contributing to the evolvement of comprehensive energy management in fully electric vehicles are also included.
This volume includes contributions on model based functional safety and fault-tolerant E/E architectures, advanced control making use of external information (from a cloud) as well and thermal management as a central part for energy optimization and finally some aspects on fuel cells.
The second volume (ISBN .....) includes chapters on ECO driving and ECO routing covering different approaches for optimal speed profiles for a given route (mostly interconnecting with cloud data).
Автор: Lalo Magni; Davide Martino Raimondo; Frank Allg?we Название: Nonlinear Model Predictive Control ISBN: 3642010938 ISBN-13(EAN): 9783642010934 Издательство: Springer Рейтинг: Цена: 22203.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Tahirovic Adnan Название: Passivity-based Model Predictive Control for Mobile Vehicle ISBN: 1447150481 ISBN-13(EAN): 9781447150480 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Passivity-based Model Predictive Control for Mobile Vehicle Navigation represents a complete theoretical approach to the adoption of passivity-based model predictive control (MPC) for autonomous vehicle navigation in both indoor and outdoor environments.
Автор: Grune Название: Nonlinear Model Predictive Control ISBN: 0857295004 ISBN-13(EAN): 9780857295002 Издательство: Springer Рейтинг: Цена: 22359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Camacho Название: Model Predictive Control ISBN: 1852336943 ISBN-13(EAN): 9781852336943 Издательство: Springer Рейтинг: Цена: 9781.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Автор: Borrelli Название: Predictive Control for Linear and Hybrid Systems ISBN: 1107016886 ISBN-13(EAN): 9781107016880 Издательство: Cambridge Academ Рейтинг: Цена: 19800.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
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