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Predictive Learning Control for Unknown Nonaffine Nonlinear Systems, Yu


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Автор: Yu
Название:  Predictive Learning Control for Unknown Nonaffine Nonlinear Systems
ISBN: 9789811988592
Издательство: Springer
Классификация:





ISBN-10: 9811988595
Обложка/Формат: Soft cover
Страницы: 206
Вес: 0.00 кг.
Дата издания: 03.03.2024
Серия: Intelligent control and learning systems
Язык: English
Издание: 1st ed. 2023
Иллюстрации: 75 illustrations, color; 2 illustrations, black and white; ix, 206 p. 77 illus., 75 illus. in color.
Размер: 235 x 155
Основная тема: Engineering
Подзаголовок: Theory and applications
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book investigates both theory and various applications of predictive learning control (PLC) which is an advanced technology for complex nonlinear systems. To avoid the difficult modeling problem for complex nonlinear systems, this book begins with the design and theoretical analysis of PLC method without using mechanism model information of the system, and then a series of PLC methods is designed that can cope with system constraints, varying trial lengths, unknown time delay, and available and unavailable system states sequentially. Applications of the PLC on both railway and urban road transportation systems are also studied. The book is intended for researchers, engineers, and graduate students who are interested in predictive control, learning control, intelligent transportation systems and related fields.
Дополнительное описание: Chapter 1: Introduction.- Chapter 2 Predictive Learning Control for Unknown Systems.- Chapter 3 Constrained Predictive Learning Control.- Chapter 4 Predictive Learning Control for Systems with Varying Trial Lengths .- Chapter 5 Predictive Learning Control



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.

Nonlinear Model Predictive Control of Combustion Engines: From Fundamentals to Applications

Автор: Albin Rajasingham Thivaharan
Название: Nonlinear Model Predictive Control of Combustion Engines: From Fundamentals to Applications
ISBN: 3030680126 ISBN-13(EAN): 9783030680121
Издательство: Springer
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Цена: 13415.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides an overview of the nonlinear model predictive control (NMPC) concept for application to innovative combustion engines. Nonlinear Model Predictive Control of Combustion Engines targets engineers and researchers in academia and industry working in the field of engine control.

Nonlinear Predictive Control Using Wiener Models: Computationally Efficient Approaches for Polynomial and Neural Structures

Автор: Lawryńczuk Maciej
Название: Nonlinear Predictive Control Using Wiener Models: Computationally Efficient Approaches for Polynomial and Neural Structures
ISBN: 3030838145 ISBN-13(EAN): 9783030838140
Издательство: Springer
Рейтинг:
Цена: 18294.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model`s structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances.

Nonlinear Model Predictive Control

Автор: Lars Gr?ne; J?rgen Pannek
Название: Nonlinear Model Predictive Control
ISBN: 3319834231 ISBN-13(EAN): 9783319834238
Издательство: Springer
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Цена: 14635.00 р.
Наличие на складе: Нет в наличии.

Описание: NMPC software both in MATLAB (R) (for smaller academic examples) and C++ (for larger examples) will be provided.

Nonlinear Model Predictive Control of Combustion Engines: From Fundamentals to Applications

Автор: Albin Rajasingham Thivaharan
Название: Nonlinear Model Predictive Control of Combustion Engines: From Fundamentals to Applications
ISBN: 3030680096 ISBN-13(EAN): 9783030680091
Издательство: Springer
Цена: 13415.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book provides an overview of the nonlinear model predictive control (NMPC) concept for application to innovative combustion engines. Nonlinear Model Predictive Control of Combustion Engines targets engineers and researchers in academia and industry working in the field of engine control.

Networked and Distributed Predictive Control

Автор: Panagiotis D. Christofides; Jinfeng Liu; David Mu?
Название: Networked and Distributed Predictive Control
ISBN: 1447126483 ISBN-13(EAN): 9781447126485
Издательство: Springer
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Цена: 12196.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book offers rigorous, yet practical, methods for the design of networked and distributed predictive control systems, including new techniques for system design, insight into likely issues and challenges, and integrated exposition of novel research topics.

Nonlinear Model Predictive Control

Автор: Frank Allg?wer; Alex Zheng
Название: Nonlinear Model Predictive Control
ISBN: 3034895542 ISBN-13(EAN): 9783034895545
Издательство: Springer
Рейтинг:
Цена: 18294.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: 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.

Robust And Adaptive Model Predictive Control Of Nonlinear Systems

Автор: Martin Guay, Veronica Adetola and Darryl De Haan
Название: Robust And Adaptive Model Predictive Control Of Nonlinear Systems
ISBN: 1849195528 ISBN-13(EAN): 9781849195522
Издательство: Неизвестно
Рейтинг:
Цена: 24944.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book offers a novel approach to adaptive control and provides a sound theoretical background to designing robust adaptive control systems with guaranteed transient performance. It focuses on the more typical role of adaptation as a means of coping with uncertainties in the system model.

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
Рейтинг:
Цена: 19377.00 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.

Nonlinear Model Predictive Control

Автор: Grune
Название: Nonlinear Model Predictive Control
ISBN: 0857295004 ISBN-13(EAN): 9780857295002
Издательство: Springer
Рейтинг:
Цена: 19514.00 р.
Наличие на складе: Нет в наличии.

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.

Nonlinear Predictive Control Using Wiener Models

Автор: ?awry?czuk
Название: Nonlinear Predictive Control Using Wiener Models
ISBN: 303083817X ISBN-13(EAN): 9783030838171
Издательство: Springer
Рейтинг:
Цена: 18294.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents computationally efficient MPC solutions. The classical model predictive control (MPC) approach to control dynamical systems described by the Wiener model uses an inverse static block to cancel the influence of process nonlinearity. Unfortunately, the model's structure is limited, and it gives poor control quality in the case of an imperfect model and disturbances. An alternative is to use the computationally demanding MPC scheme with on-line nonlinear optimisation repeated at each sampling instant. A linear approximation of the Wiener model or the predicted trajectory is found on-line. As a result, quadratic optimisation tasks are obtained. Furthermore, parameterisation using Laguerre functions is possible to reduce the number of decision variables. Simulation results for ten benchmark processes show that the discussed MPC algorithms lead to excellent control quality. For a neutralisation reactor and a fuel cell, essential advantages of neural Wiener models are demonstrated.

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
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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