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Neural Networks for Modelling and Control of Dynamic Systems / A Practitioner`s Handbook, Norgaard M., Ravn O., Poulsen N.K., Hansen L.K.



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Автор: Norgaard M., Ravn O., Poulsen N.K., Hansen L.K.
Название:  Neural Networks for Modelling and Control of Dynamic Systems / A Practitioner`s Handbook
Издательство: Springer
Классификация:
Проектирование
Проектирование электроники
Искусственный интеллект
Компьютерное моделирование

ISBN: 1852332271
ISBN-13(EAN): 9781852332273
ISBN: 1-85233-227-1
ISBN-13(EAN): 978-1-85233-227-3
Обложка/Формат: Paperback
Страницы: 260
Вес: 0.42 кг.
Дата издания: 10.02.2003
Серия: Advanced textbooks in control and signal processing
Язык: English
Издание: 1st ed. 2000. corr.
Иллюстрации: 33 illustrations, black and white; xiv, 246 p. 33 illus.
Размер: 23.39 x 15.60 x 1.40
Читательская аудитория: Professional & vocational
Подзаголовок: A practitioner`s handbook
Ссылка на Издательство: Link
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Поставляется из: Германии
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.
Дополнительное описание: Илюстрации: 84
Круг читателей: Graduate students, practitioners, scientists
Язык: eng
Издание: 1st ed. 2000. Corr. 3rd p
Оглавление: Introduction.- System Identification with Neural Networks.- Control with Neural Networks.- Case Studies.- References.- Index.





Control of Electric Machine Drive Systems

Автор: Sul
Название: Control of Electric Machine Drive Systems
ISBN: 0470590793 ISBN-13(EAN): 9780470590799
Издательство: Wiley
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Цена: 14438 р.
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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.

Plausible Neural Networks for Biological Modelling

Автор: Mastebroek H.A., Vos J.E.
Название: Plausible Neural Networks for Biological Modelling
ISBN: 0792371925 ISBN-13(EAN): 9780792371922
Издательство: Springer
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Цена: 14629 р.
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Описание: This book has the unique intention of returning the mathematical tools of neural networks to the biological realm of the nervous system, where they originated a few decades ago. It aims to introduce, in a didactic manner, two relatively recent developments in neural network methodology, namely recurrence in the architecture and the use of spiking or integrate-and-fire neurons. In addition, the neuro-anatomical processes of synapse modification during development, training, and memory formation are discussed as realistic bases for weight-adjustment in neural networks. While neural networks have many applications outside biology, where it is irrelevant precisely which architecture and which algorithms are used, it is essential that there is a close relationship between the network's properties and whatever is the case in a neuro-biological phenomenon that is being modelled or simulated in terms of a neural network. A recurrent architecture, the use of spiking neurons and appropriate weight update rules contribute to the plausibility of a neural network in such a case. Therefore, in the first half of this book the foundations are laid for the application of neural networks as models for the various biological phenomena that are treated in the second half of this book. These include various neural network models of sensory and motor control tasks that implement one or several of the requirements for biological plausibility.

Geometrical Dynamics of Complex Systems / A Unified Modelling Approach to Physics, Control, Biomechanics, Neurodynamics and Psycho-Socio-Economical Dynamics

Автор: Ivancevic Vladimir G., Ivancevic Tijana T.
Название: Geometrical Dynamics of Complex Systems / A Unified Modelling Approach to Physics, Control, Biomechanics, Neurodynamics and Psycho-Socio-Economical Dynamics
ISBN: 1402045441 ISBN-13(EAN): 9781402045448
Издательство: Springer
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Цена: 29298 р.
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Описание: This volume presents a comprehensive introduction into rigorous geometrical dynamics of complex systems of various natures. By "complex systems", in this book are meant high-dimensional nonlinear systems, which can be (but not necessarily are) adaptive. This monograph proposes a unified geometrical approach to dynamics of complex systems of various kinds: engineering, physical, biophysical, psychophysical, sociophysical, econophysical, etc. As their names suggest, all these multi-input multi-output (MIMO) systems have something in common: the underlying physics. Using sophisticated machinery composed of differential geometry, topology and path integrals, this book proposes a unified approach to complex dynamics – of predictive power much greater than the currently popular "soft-science" approach to complex systems. The main objective of this book is to show that high-dimensional nonlinear systems in "real life" can be modeled and analyzed using rigorous mathematics, which enables their complete predictability and controllability, as if they were linear systems.The book has two chapters and an appendix. The first chapter develops the geometrical machinery in both an intuitive and rigorous manner. The second chapter applies this geometrical machinery to a number of examples of complex systems, including mechanical, physical, control, biomechanical, robotic, neurodynamical and psycho-social-economical systems. The appendix gives all the necessary background for comprehensive reading of this book.

Modelling and Control for Intelligent Industrial Systems

Автор: Rigatos
Название: Modelling and Control for Intelligent Industrial Systems
ISBN: 364217874X ISBN-13(EAN): 9783642178740
Издательство: Springer
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Цена: 19532 р.
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Описание:  Incorporating intelligence in industrial systems can help to increase productivity, cut-off production costs, and to improve working conditions and safety in industrial environments. This need has resulted in the rapid development of modeling and control methods for industrial systems and robots, of fault detection and isolation methods for the prevention of critical situations in industrial work-cells and production plants, of optimization methods aiming at a more profitable functioning of industrial installations and robotic devices and of machine intelligence methods aiming at reducing human intervention in industrial systems operation.To this end, the book analyzes and extends some main directions of research in modeling and control for industrial systems. These are: (i) industrial robots, (ii) mobile robots and autonomous vehicles, (iii) adaptive and robust control of electromechanical systems, (iv) filtering and stochastic estimation for multisensor fusion and sensorless control of industrial systems (iv) fault detection and isolation in robotic and industrial systems, (v) optimization in industrial automation and robotic systems design, and (vi) machine intelligence for robots autonomy. The book will be a useful companion to engineers and researchers since it covers a wide spectrum of problems in the area of industrial systems. Moreover, the book is addressed to undergraduate and post-graduate students, as an upper-level course supplement of automatic control and robotics courses.

Flexible AC Transmission Systems: Modelling and Control

Автор: Xiao-Ping Zhang; Christian Rehtanz; Bikash Pal
Название: Flexible AC Transmission Systems: Modelling and Control
ISBN: 364244508X ISBN-13(EAN): 9783642445088
Издательство: Springer
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Цена: 17578 р.
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Описание:

The extended and revised second edition of this successful monograph presents advanced modeling, analysis and control techniques of Flexible AC Transmission Systems (FACTS). The book covers comprehensively a range of power-system control problems: from steady-state voltage and power flow control, to voltage and reactive power control, to voltage stability control, to small signal stability control using FACTS controllers.

In the six years since the first edition of the book has been published research on the FACTS has continued to flourish while renewable energy has developed into a mature and booming global green business. The second edition reflects the new developments in converter configuration, smart grid technologies, super power grid developments worldwide, new approaches for FACTS control design, new controllers for distribution system control, and power electronic controllers in wind generation operation and control. The latest trends of VSC-HVDC with multilevel architecture have been included and four completely new chapters have been added devoted to Multi-Agent Systems for Coordinated Control of FACTS-devices, Power System Stability Control using FACTS with Multiple Operating Points, Control of a Looping Device in a Distribution System, and Power Electronic Control for Wind Generation.

Bond Graphs for Modelling, Control and Fault Diagnosis of Engineering Systems

Автор: Wolfgang Borutzky
Название: Bond Graphs for Modelling, Control and Fault Diagnosis of Engineering Systems
ISBN: 3319474332 ISBN-13(EAN): 9783319474335
Издательство: Springer
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Цена: 20899 р.
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Описание: This compilation of contributions from experts across the world addresses readers in academia and industry who are concerned with control system design. It covers theoretical topics, applications in various areas as well as software for bond graph modelling.

Modelling and Control in Biomedical Systems 2006,

Автор: David Dagan Feng
Название: Modelling and Control in Biomedical Systems 2006,
ISBN: 0080445306 ISBN-13(EAN): 9780080445304
Издательство: Elsevier Science
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Цена: 10973 р.
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Описание: Contains the 92 papers that were presented by their authors at the symposium on Modelling and Control in Biomedical Systems that was held in Reims, France, 20-22 August 2006.

Handbook of Control Systems Engineering

Автор: Westphal Louis C.
Название: Handbook of Control Systems Engineering
ISBN: 0792374940 ISBN-13(EAN): 9780792374947
Издательство: Springer
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Цена: 41696 р.
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Описание: This book is a revision and extension of the author's 1995 Sourcebook of Control Systems Engineering. Because of the extensions and other modifications, it has been re-titled Handbook of Control Systems Engineering, which it is intended to be for its prime audience: advanced undergraduate students, beginning graduate students, and practicing engineers needing an understandable review of the field or recent developments which may prove useful. New in This Edition. Two new chapters on aspects of nonlinear systems have been incorporated. In the first of these, selected material for nonlinear systems is concentrated on four aspects: showing the value of certain linear controllers, arguing the suitability of algebraic linearization, reviewing the semi-classical methods of harmonic balance, and introducing the nonlinear change of variable technique known as feedback linearization. In the second new chapter, the topic of variable structure control, often with sliding mode, is introduced. A third chapter introduces discrete event systems, including several approaches to their analysis. The chapters on robust control and intelligent control have been extensively revised. Modest revisions and extensions have also been made to other chapters, often to incorporate extensions to nonlinear systems. Many references have been updated to more recent books, although old standards are still cited. Also, some of the advances in computer and communications technology are reflected. The index has been revised and expanded. The structure of the book is as in the first edition. Briefly, the aim is to present the topics in a fairly modular manner with certain main groupings. The first several chapters are concerned with the hardware and software of the control task as well as systems engineering associated with the selection of appropriate components. The next chapters look at the sources and representations of the mathematical models used in the theory. A number of chapters then are concerned with standard classical or transform domain material as is usually presented in a first level university course, including stability theory, root locus diagrams, and Bode plots. The next group of chapters concerns the standard modern or state space material usually met in a second level course. Included here are observers, pole placement, and optimal control. Overlapping into usual graduate level courses are the next several chapters on more advanced optimal control, Kalman filtering, system identification, and standard adaptive control. The final chapters introduce more advanced, research level subjects. Here are selected topics in nonlinear control, intelligent control, robust control, and discrete event systems. The topics covered are intended to represent the mainstream of control systems teaching. Examples are presented to illustrate the computability of the theory presented. Handbook of Controls Systems Engineering, Second Edition is suitable as a secondary text for upper level undergraduate students, beginning graduate students, and as a reference for researchers and practitioners in industry.

Handbook of Defeasible Reasoning and Uncertainty Management Systems / Volume 7: Agent-Based Defeasible Control in Dynamic Environments

Автор: Meyer John-Jules Ch., Treur Jan
Название: Handbook of Defeasible Reasoning and Uncertainty Management Systems / Volume 7: Agent-Based Defeasible Control in Dynamic Environments
ISBN: 1402008341 ISBN-13(EAN): 9781402008344
Издательство: Springer
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Цена: 26334 р.
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Описание: This last volume of the Handbook of Defeasible Reasoning and Uncertainty Management Systems is - together with Volume 6 - devoted to the topics Reasoning and Dynamics, covering both the topics of "Dynamics of Reasoning", where reasoning is viewed as a process, and "Reasoning about Dynamics", which must be understood as pertaining to how both designers of, and agents within dynamic systems may reason about these systems. The present volume presents work done in this context and is more focused on "reasoning about dynamics", viz. how (human and artificial) agents reason about (systems in) dynamic environments in order to control them. In particular modelling frameworks and generic agent models for modelling these dynamic systems and formal approaches to these systems such as logics for agents and formal means to reason about agent-based and compositional systems, and action & change more in general are considered.

A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems

Название: A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
ISBN: 1849968675 ISBN-13(EAN): 9781849968676
Издательство: Springer
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Цена: 17578 р.
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Описание: How does a machine learn a new concept on the basis of examples? This second edition takes account of important new developments in the field. It also deals extensively with the theory of learning control systems, now comparably mature to learning of neural networks.

Design and Control of Intelligent Robotic Systems

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
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Цена: 27345 р.
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Описание: With the increasing applications of intelligent robotic systems in various fields, the design and control of these systems have increasingly attracted interest from researchers. This book presents a collection of some advanced research on design and control of intelligent robots. It is suitable for engineers, researchers, and graduate students.

Cellular Neural Networks: Dynamics and Modelling

Автор: Slavova A.
Название: Cellular Neural Networks: Dynamics and Modelling
ISBN: 140201192X ISBN-13(EAN): 9781402011924
Издательство: Springer
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Цена: 15625 р.
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Описание: This book deals with new theoretical results for studying Cellular Neural Networks (CNNs) concerning its dynamical behavior. New aspects of CNNs' applications are developed for modelling of some famous nonlinear partial differential equations arising in biology, genetics, neurophysiology, physics, ecology, etc. The analysis of CNNs' models is based on the harmonic balance method well known in control theory and in the study of electronic oscillators. Such phenomena as hysteresis, bifurcation and chaos are studied for CNNs. The topics investigated in the book involve several scientific disciplines, such as dynamical systems, applied mathematics, mathematical modelling, information processing, biology and neurophysiology. The reader will find comprehensive discussion on the subject as well as rigorous mathematical analyses of networks of neurons from the view point of dynamical systems. The text is written as a textbook for senior undergraduate and graduate students in applied mathematics. Providing a summary of recent results on dynamics and modelling of CNNs, the book will also be of interest to all researchers in the area.


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