Автор: Dikai Liu; Lingfeng Wang; Kay Chen Tan (Eds.) Название: Design and Control of Intelligent Robotic Systems ISBN: 3540899324 ISBN-13(EAN): 9783540899327 Издательство: Springer Рейтинг: Цена: 36570.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: With the increasing applications of intelligent robotic systems in various ?elds, the - sign and control of these systems have increasingly attracted interest from researchers.
Автор: Yan Название: Variable Structure Control of Complex Systems ISBN: 3319489615 ISBN-13(EAN): 9783319489612 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book systematizes recent research work on variable-structure control. It is self-contained, presenting necessary mathematical preliminaries so that the theoretical developments can be easily understood by a broad readership.The text begins with an introduction to the fundamental ideas of variable-structure control pertinent to their application in complex nonlinear systems. In the core of the book, the authors lay out an approach, suitable for a large class of systems, that deals with system uncertainties with nonlinear bounds. Its treatment of complex systems in which limited measurement information is available makes the results developed convenient to implement. Various case-study applications are described, from aerospace, through power systems to river pollution control with supporting simulations to aid the transition from mathematical theory to engineering practicalities.The book addresses systems with nonlinearities, time delays and interconnections and considers issues such as stabilization, observer design, and fault detection and isolation. It makes extensive use of numerical and practical examples to render its ideas more readily absorbed.Variable-Structure Control of Complex Systems will be of interest to academic researchers studying control theory and its application in nonlinear, time-delayed an modular large-scale systems; the robustness of its approach will also be attractive to control engineers working in industries associate with aerospace, electrical and mechanical engineering.
Автор: Sul Название: Control of Electric Machine Drive Systems ISBN: 0470590793 ISBN-13(EAN): 9780470590799 Издательство: Wiley Рейтинг: Цена: 20901.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on the author`s industry experience and collaborative works with other industries, Control of Electric Machine Drive System is packed with implemented, tested, and verified ideas that relate to everyday problems in the field.
Автор: Jagannathan, Sarangapani Название: Control of Complex Systems ISBN: 0128052465 ISBN-13(EAN): 9780128052464 Издательство: Elsevier Science Рейтинг: Цена: 23244.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: "Introduction and Background on Control Theory," "Adaptive Control and Neuroscience," "Adaptive Learning Algorithms," "Cyber-Physical Systems and Cooperative Control," "Applications." The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists.
This book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems, including Electrical Engineers, Computer Science Engineers, Mechanical Engineers, Aerospace/Automotive Engineers, and Industrial Engineers. It could be used as a text or reference for advanced courses in complex control systems.
- Collection of chapters from several well-known professors and researchers that will showcase their recent work
- Presents different state-of-the-art control approaches and theory for complex systems
- Gives algorithms that take into consideration the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams
- Real system examples and figures throughout, make ideas concrete
Includes chapters from several well-known professors and researchers that showcases their recent work
Presents different state-of-the-art control approaches and theory for complex systems
Explores the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals, and malicious attacks compromising the security of networked teams
Serves as a helpful reference for researchers and control engineers working with machine learning, adaptive control, and automatic control systems
Описание: The technology of neural networks has attracted much attention in recent years. Their ability to learn nonlinear relationships is widely appreciated and is utilized in many different types of applications; modelling of dynamic systems, signal processing, and control system design being some of the most common. The theory of neural computing has matured considerably over the last decade and many problems of neural network design, training and evaluation have been resolved. This book provides a comprehensive introduction to the most popular class of neural network, the multilayer perceptron, and shows how it can be used for system identification and control. It aims to provide the reader with a sufficient theoretical background to understand the characteristics of different methods, to be aware of the pit-falls and to make proper decisions in all situations. The subjects treated include: System identification: multilayer perceptrons; how to conduct informative experiments; model structure selection; training methods; model validation; pruning algorithms. Control: direct inverse, internal model, feedforward, optimal and predictive control; feedback linearization and instantaneous-linearization-based controllers. Case studies: prediction of sunspot activity; modelling of a hydraulic actuator; control of a pneumatic servomechanism; water-level control in a conical tank. The book is very application-oriented and gives detailed and pragmatic recommendations that guide the user through the plethora of methods suggested in the literature. Furthermore, it attempts to introduce sound working procedures that can lead to efficient neural network solutions. This will make the book invaluable to the practitioner and as a textbook in courses with a significant hands-on component.
ООО "Логосфера " Тел:+7(495) 980-12-10 www.logobook.ru
