Hybrid Systems, Optimal Control and Hybrid Vehicles, Thomas J. B?hme; Benjamin Frank
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: 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.
Автор: Hao Yang; Bin Jiang; Vincent Cocquempot Название: Fault Tolerant Control Design for Hybrid Systems ISBN: 3642106803 ISBN-13(EAN): 9783642106804 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides readers a good understanding on how to achieve Fault Tolerant Control goal of Hybrid Systems. It presents important theoretical results as well as their applications.
Автор: Yuan Zou; Junqiu Li; Xiaosong Hu; Yann Chamaillard Название: Modeling and Control of Hybrid Propulsion System for Ground Vehicles ISBN: 3662585502 ISBN-13(EAN): 9783662585504 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the systematic design of architectures, parameters and control of typical hybrid propulsion systems for wheeled and tracked vehicles based on a combination of theoretical research and engineering practice. Adopting a mechatronic system dynamics perspective, principles and methods from the fields of optimal control and system optimization are applied in order to analyze the hybrid propulsion configuration and controller design. Case investigations for typical hybrid propulsion systems of wheeled and tracked ground vehicles are also provided.
Автор: Amir Taghavipour; Mahyar Vajedi; Nasser L. Azad Название: Intelligent Control of Connected Plug-in Hybrid Electric Vehicles ISBN: 3030003132 ISBN-13(EAN): 9783030003135 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Поставка под заказ.
Описание: Intelligent Control of Connected Plug-in Hybrid Electric Vehicles presents the development of real-time intelligent control systems for plug-in hybrid electric vehicles, which involves control-oriented modelling, controller design, and performance evaluation. The controllers outlined in the book take advantage of advances in vehicle communications technologies, such as global positioning systems, intelligent transportation systems, geographic information systems, and other on-board sensors, in order to provide look-ahead trip data. The book contains simple and efficient models and fast optimization algorithms for the devised controllers to address the challenge of real-time implementation in the design of complex control systems. Using the look-ahead trip information, the authors of the book propose intelligent optimal model-based control systems to minimize the total energy cost, for both grid-derived electricity and fuel. The multilayer intelligent control system proposed consists of trip planning, an ecological cruise controller, and a route-based energy management system. An algorithm that is designed to take advantage of previewed trip information to optimize battery depletion profiles is presented in the book. Different control strategies are compared and ways in which connecting vehicles via vehicle-to-vehicle communication can improve system performance are detailed. Intelligent Control of Connected Plug-in Hybrid Electric Vehicles is a useful source of information for postgraduate students and researchers in academic institutions participating in automotive research activities. Engineers and designers working in research and development for automotive companies will also find this book of interest.Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Автор: Bram de Jager; Thijs van Keulen; John Kessels Название: Optimal Control of Hybrid Vehicles ISBN: 1447150759 ISBN-13(EAN): 9781447150756 Издательство: Springer Рейтинг: Цена: 16979.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a description of power train control for hybrid vehicles. Coverage includes real-time-implementable strategies that can approximate an optimal solution, including one that is adaptive for vehicle conditions like velocity and mass.
Автор: Bram de Jager; Thijs van Keulen; John Kessels Название: Optimal Control of Hybrid Vehicles ISBN: 1447159888 ISBN-13(EAN): 9781447159889 Издательство: Springer Рейтинг: Цена: 15672.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a description of power train control for hybrid vehicles. Coverage includes real-time-implementable strategies that can approximate an optimal solution, including one that is adaptive for vehicle conditions like velocity and mass.
Название: Energy systems for electric and hybrid vehicles ISBN: 1785610082 ISBN-13(EAN): 9781785610080 Издательство: Неизвестно Рейтинг: Цена: 30577.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Electric and hybrid vehicles have been globally identified to be the most environmental friendly road transportation. Energy Systems for Electric and Hybrid Vehicles provides comprehensive coverage of the three main energy system technologies of these vehicles - energy sources, battery charging and vehicle-to-grid systems.
Автор: Yuan Zou; Yann Chamaillard; Xiaosong Hu Название: Modeling and Control of Hybrid Propulsion for Ground Vehicles ISBN: 3662536714 ISBN-13(EAN): 9783662536711 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on the systematic design of architectures, parameters and control of typical hybrid propulsion systems for wheeled and tracked vehicles based on a combination of theoretical research and engineering practice.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Powertrain electrification, fuel decarburization, and energy diversification are techniques that are spreading all over the world, leading to cleaner and more efficient vehicles.
Hybrid electric vehicles (HEVs) are considered a promising technology today to address growing air pollution and energy deprivation. To realize these gains and still maintain good performance, it is critical for HEVs to have sophisticated energy management systems. Supervised by such a system, HEVs could operate in different modes, such as full electric mode and power split mode. Hence, researching and constructing advanced energy management strategies (EMSs) is important for HEVs performance. There are a few books about rule- and optimization-based approaches for formulating energy management systems. Most of them concern traditional techniques and their efforts focus on searching for optimal control policies offline. There is still much room to introduce learning-enabled energy management systems founded in artificial intelligence and their real-time evaluation and application.
In this book, a series hybrid electric vehicle was considered as the powertrain model, to describe and analyze a reinforcement learning (RL)-enabled intelligent energy management system. The proposed system can not only integrate predictive road information but also achieve online learning and updating. Detailed powertrain modeling, predictive algorithms, and online updating technology are involved, and evaluation and verification of the presented energy management system is conducted and executed.
Автор: Amir Taghavipour; Mahyar Vajedi; Nasser L. Azad Название: Intelligent Control of Connected Plug-in Hybrid Electric Vehicles ISBN: 3030131017 ISBN-13(EAN): 9783030131012 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Поставка под заказ.
Описание: Intelligent Control of Connected Plug-in Hybrid Electric Vehicles presents the development of real-time intelligent control systems for plug-in hybrid electric vehicles, which involves control-oriented modelling, controller design, and performance evaluation. The controllers outlined in the book take advantage of advances in vehicle communications technologies, such as global positioning systems, intelligent transportation systems, geographic information systems, and other on-board sensors, in order to provide look-ahead trip data. The book contains simple and efficient models and fast optimization algorithms for the devised controllers to address the challenge of real-time implementation in the design of complex control systems. Using the look-ahead trip information, the authors of the book propose intelligent optimal model-based control systems to minimize the total energy cost, for both grid-derived electricity and fuel. The multilayer intelligent control system proposed consists of trip planning, an ecological cruise controller, and a route-based energy management system. An algorithm that is designed to take advantage of previewed trip information to optimize battery depletion profiles is presented in the book. Different control strategies are compared and ways in which connecting vehicles via vehicle-to-vehicle communication can improve system performance are detailed. Intelligent Control of Connected Plug-in Hybrid Electric Vehicles is a useful source of information for postgraduate students and researchers in academic institutions participating in automotive research activities. Engineers and designers working in research and development for automotive companies will also find this book of interest.Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
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