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Nonlinear Networks And Systems
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Book Synopsis Synchronization in Complex Networks of Nonlinear Dynamical Systems by : Chai Wah Wu
Download or read book Synchronization in Complex Networks of Nonlinear Dynamical Systems written by Chai Wah Wu and published by World Scientific. This book was released on 2007 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together two emerging research areas: synchronization in coupled nonlinear systems and complex networks, and study conditions under which a complex network of dynamical systems synchronizes. While there are many texts that study synchronization in chaotic systems or properties of complex networks, there are few texts that consider the intersection of these two very active and interdisciplinary research areas. The main theme of this book is that synchronization conditions can be related to graph theoretical properties of the underlying coupling topology. The book introduces ideas from systems theory, linear algebra and graph theory and the synergy between them that are necessary to derive synchronization conditions. Many of the results, which have been obtained fairly recently and have until now not appeared in textbook form, are presented with complete proofs. This text is suitable for graduate-level study or for researchers who would like to be better acquainted with the latest research in this area. Sample Chapter(s). Chapter 1: Introduction (76 KB). Contents: Graphs, Networks, Laplacian Matrices and Algebraic Connectivity; Graph Models; Synchronization in Networks of Nonlinear Continuous-Time Dynamical Systems; Synchronization in Networks of Coupled Discrete-Time Systems; Synchronization in Network of Systems with Linear Dynamics; Agreement and Consensus Problems in Groups of Interacting Agents. Readership: Graduate students and researchers in physics, applied mathematics and engineering.
Book Synopsis Theory of Nonlinear Networks and Systems by : Thomas E. Stern
Download or read book Theory of Nonlinear Networks and Systems written by Thomas E. Stern and published by . This book was released on 1965 with total page 616 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonlinear networks and systems by : Richard Clay
Download or read book Nonlinear networks and systems written by Richard Clay and published by . This book was released on 1984 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonlinear System Identification by : Oliver Nelles
Download or read book Nonlinear System Identification written by Oliver Nelles and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 785 pages. Available in PDF, EPUB and Kindle. Book excerpt: Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.
Book Synopsis Neural Network Control of Nonlinear Discrete-Time Systems by : Jagannathan Sarangapani
Download or read book Neural Network Control of Nonlinear Discrete-Time Systems written by Jagannathan Sarangapani and published by CRC Press. This book was released on 2018-10-03 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent systems are a hallmark of modern feedback control systems. But as these systems mature, we have come to expect higher levels of performance in speed and accuracy in the face of severe nonlinearities, disturbances, unforeseen dynamics, and unstructured uncertainties. Artificial neural networks offer a combination of adaptability, parallel processing, and learning capabilities that outperform other intelligent control methods in more complex systems. Borrowing from Biology Examining neurocontroller design in discrete-time for the first time, Neural Network Control of Nonlinear Discrete-Time Systems presents powerful modern control techniques based on the parallelism and adaptive capabilities of biological nervous systems. At every step, the author derives rigorous stability proofs and presents simulation examples to demonstrate the concepts. Progressive Development After an introduction to neural networks, dynamical systems, control of nonlinear systems, and feedback linearization, the book builds systematically from actuator nonlinearities and strict feedback in nonlinear systems to nonstrict feedback, system identification, model reference adaptive control, and novel optimal control using the Hamilton-Jacobi-Bellman formulation. The author concludes by developing a framework for implementing intelligent control in actual industrial systems using embedded hardware. Neural Network Control of Nonlinear Discrete-Time Systems fosters an understanding of neural network controllers and explains how to build them using detailed derivations, stability analysis, and computer simulations.
Book Synopsis Identification of Nonlinear Systems Using Neural Networks and Polynomial Models by : Andrzej Janczak
Download or read book Identification of Nonlinear Systems Using Neural Networks and Polynomial Models written by Andrzej Janczak and published by Springer Science & Business Media. This book was released on 2004-11-18 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph systematically presents the existing identification methods of nonlinear systems using the block-oriented approach It surveys various known approaches to the identification of Wiener and Hammerstein systems which are applicable to both neural network and polynomial models. The book gives a comparative study of their gradient approximation accuracy, computational complexity, and convergence rates and furthermore presents some new and original methods concerning the model parameter adjusting with gradient-based techniques. "Identification of Nonlinear Systems Using Neural Networks and Polynomal Models" is useful for researchers, engineers and graduate students in nonlinear systems and neural network theory.
Book Synopsis Artificial Neural Networks for Modelling and Control of Non-Linear Systems by : Johan A.K. Suykens
Download or read book Artificial Neural Networks for Modelling and Control of Non-Linear Systems written by Johan A.K. Suykens and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights. However, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result. Artificial Neural Networks for Modelling and Control of Non-Linear Systems investigates the subject from a system theoretical point of view. However the mathematical theory that is required from the reader is limited to matrix calculus, basic analysis, differential equations and basic linear system theory. No preliminary knowledge of neural networks is explicitly required. The book presents both classical and novel network architectures and learning algorithms for modelling and control. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems. A major contribution of this book is to introduce NLq Theory as an extension towards modern control theory, in order to analyze and synthesize non-linear systems that contain linear together with static non-linear operators that satisfy a sector condition: neural state space control systems are an example. Moreover, it turns out that NLq Theory is unifying with respect to many problems arising in neural networks, systems and control. Examples show that complex non-linear systems can be modelled and controlled within NLq theory, including mastering chaos. The didactic flavor of this book makes it suitable for use as a text for a course on Neural Networks. In addition, researchers and designers will find many important new techniques, in particular NLq emTheory, that have applications in control theory, system theory, circuit theory and Time Series Analysis.
Book Synopsis Neural Network-Based State Estimation of Nonlinear Systems by : Heidar A. Talebi
Download or read book Neural Network-Based State Estimation of Nonlinear Systems written by Heidar A. Talebi and published by Springer. This book was released on 2009-12-04 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises.
Book Synopsis Introduction to Nonlinear Circuits and Networks by : Bharathwaj Muthuswamy
Download or read book Introduction to Nonlinear Circuits and Networks written by Bharathwaj Muthuswamy and published by Springer. This book was released on 2018-10-26 with total page 373 pages. Available in PDF, EPUB and Kindle. Book excerpt: This course-based text revisits classic concepts in nonlinear circuit theory from a very much introductory point of view: the presentation is completely self-contained and does not assume any prior knowledge of circuit theory. It is simply assumed that readers have taken a first-year undergraduate course in differential and integral calculus, along with an elementary physics course in classical mechanics and electrodynamics. Further, it discusses topics not typically found in standard textbooks, such as nonlinear operational amplifier circuits, nonlinear chaotic circuits and memristor networks. Each chapter includes a set of illustrative and worked examples, along with end-of-chapter exercises and lab exercises using the QUCS open-source circuit simulator. Solutions and other material are provided on the YouTube channel created for this book by the authors.
Book Synopsis Theory of nonlinear networks and systems ; and introduction by : Thomas E. Sterns
Download or read book Theory of nonlinear networks and systems ; and introduction written by Thomas E. Sterns and published by . This book was released on 1965 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Nonlinear Circuits and Systems with Memristors by : Fernando Corinto
Download or read book Nonlinear Circuits and Systems with Memristors written by Fernando Corinto and published by Springer Nature. This book was released on 2020-10-31 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a new approach to the study of physical nonlinear circuits and advanced computing architectures with memristor devices. Such a unified approach to memristor theory has never been systematically presented in book form. After giving an introduction on memristor-based nonlinear dynamical circuits (e.g., periodic/chaotic oscillators) and their use as basic computing analogue elements, the authors delve into the nonlinear dynamical properties of circuits and systems with memristors and present the flux-charge analysis, a novel method for analyzing the nonlinear dynamics starting from writing Kirchhoff laws and constitutive relations of memristor circuit elements in the flux-charge domain. This analysis method reveals new peculiar and intriguing nonlinear phenomena in memristor circuits, such as the coexistence of different nonlinear dynamical behaviors, extreme multistability and bifurcations without parameters. The book also describes how arrays of memristor-based nonlinear oscillators and locally-coupled neural networks can be applied in the field of analog computing architectures, for example for pattern recognition. The book will be of interest to scientists and engineers involved in the conceptual design of physical memristor devices and systems, mathematical and circuit models of physical processes, circuits and networks design, system engineering, or data processing and system analysis.
Book Synopsis Nonlinear Control of Dynamic Networks by : Tengfei Liu
Download or read book Nonlinear Control of Dynamic Networks written by Tengfei Liu and published by CRC Press. This book was released on 2014-04-07 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Significant progress has been made on nonlinear control systems in the past two decades. However, many of the existing nonlinear control methods cannot be readily used to cope with communication and networking issues without nontrivial modifications. For example, small quantization errors may cause the performance of a "well-designed" nonlinear control system to deteriorate. Motivated by the need for new tools to solve complex problems resulting from smart power grids, biological processes, distributed computing networks, transportation networks, robotic systems, and other cutting-edge control applications, Nonlinear Control of Dynamic Networks tackles newly arising theoretical and real-world challenges for stability analysis and control design, including nonlinearity, dimensionality, uncertainty, and information constraints as well as behaviors stemming from quantization, data-sampling, and impulses. Delivering a systematic review of the nonlinear small-gain theorems, the text: Supplies novel cyclic-small-gain theorems for large-scale nonlinear dynamic networks Offers a cyclic-small-gain framework for nonlinear control with static or dynamic quantization Contains a combination of cyclic-small-gain and set-valued map designs for robust control of nonlinear uncertain systems subject to sensor noise Presents a cyclic-small-gain result in directed graphs and distributed control of nonlinear multi-agent systems with fixed or dynamically changing topology Based on the authors’ recent research, Nonlinear Control of Dynamic Networks provides a unified framework for robust, quantized, and distributed control under information constraints. Suggesting avenues for further exploration, the book encourages readers to take into consideration more communication and networking issues in control designs to better handle the arising challenges.
Download or read book Nonlinear Systems written by P. G. Drazin and published by Cambridge University Press. This book was released on 1992-06-26 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: The theories of bifurcation, chaos and fractals as well as equilibrium, stability and nonlinear oscillations, are part of the theory of the evolution of solutions of nonlinear equations. A wide range of mathematical tools and ideas are drawn together in the study of these solutions, and the results applied to diverse and countless problems in the natural and social sciences, even philosophy. The text evolves from courses given by the author in the UK and the United States. It introduces the mathematical properties of nonlinear systems, mostly difference and differential equations, as an integrated theory, rather than presenting isolated fashionable topics. Topics are discussed in as concrete a way as possible and worked examples and problems are used to explain, motivate and illustrate the general principles. The essence of these principles, rather than proof or rigour, is emphasized. More advanced parts of the text are denoted by asterisks, and the mathematical prerequisites are limited to knowledge of linear algebra and advanced calculus, thus making it ideally suited to both senior undergraduates and postgraduates from physics, engineering, chemistry, meteorology etc. as well as mathematics.
Book Synopsis Intelligent Observer and Control Design for Nonlinear Systems by : Dierk Schröder
Download or read book Intelligent Observer and Control Design for Nonlinear Systems written by Dierk Schröder and published by Springer Science & Business Media. This book was released on 2013-04-17 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: This application-oriented monograph focuses on a novel and complex type of control systems. Written on an engineering level, including fundamentals, advanced methods and applications, the book applies techniques originating from new methods such as artificial intelligence, fuzzy logic, neural networks etc.
Book Synopsis Dynamics of Nonlinear Time-Delay Systems by : Muthusamy Lakshmanan
Download or read book Dynamics of Nonlinear Time-Delay Systems written by Muthusamy Lakshmanan and published by Springer Science & Business Media. This book was released on 2011-01-04 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Synchronization of chaotic systems, a patently nonlinear phenomenon, has emerged as a highly active interdisciplinary research topic at the interface of physics, biology, applied mathematics and engineering sciences. In this connection, time-delay systems described by delay differential equations have developed as particularly suitable tools for modeling specific dynamical systems. Indeed, time-delay is ubiquitous in many physical systems, for example due to finite switching speeds of amplifiers in electronic circuits, finite lengths of vehicles in traffic flows, finite signal propagation times in biological networks and circuits, and quite generally whenever memory effects are relevant. This monograph presents the basics of chaotic time-delay systems and their synchronization with an emphasis on the effects of time-delay feedback which give rise to new collective dynamics. Special attention is devoted to scalar chaotic/hyperchaotic time-delay systems, and some higher order models, occurring in different branches of science and technology as well as to the synchronization of their coupled versions. Last but not least, the presentation as a whole strives for a balance between the necessary mathematical description of the basics and the detailed presentation of real-world applications.
Book Synopsis Nonlinear Pinning Control of Complex Dynamical Networks by : Edgar N. Sanchez
Download or read book Nonlinear Pinning Control of Complex Dynamical Networks written by Edgar N. Sanchez and published by CRC Press. This book was released on 2021-08-19 with total page 228 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents two nonlinear control strategies for complex dynamical networks. First, sliding-mode control is used, and then the inverse optimal control approach is employed. For both cases, model-based is considered in Chapter 3 and Chapter 5; then, Chapter 4 and Chapter 6 are based on determining a model for the unknow system using a recurrent neural network, using on-line extended Kalman filtering for learning. The book is organized in four sections. The first one covers mathematical preliminaries, with a brief review for complex networks, and the pinning methodology. Additionally, sliding-mode control and inverse optimal control are introduced. Neural network structures are also discussed along with a description of the high-order ones. The second section presents the analysis and simulation results for sliding-mode control for identical as well as non-identical nodes. The third section describes analysis and simulation results for inverse optimal control considering identical or non-identical nodes. Finally, the last section presents applications of these schemes, using gene regulatory networks and microgrids as examples.
Book Synopsis Nonlinear Identification and Control by : G.P. Liu
Download or read book Nonlinear Identification and Control written by G.P. Liu and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The purpose of this monograph is to give the broad aspects of nonlinear identification and control using neural networks. It uses a number of simulated and industrial examples throughout, to demonstrate the operation of nonlinear identification and control techniques using neural networks.
