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Author : M. Norgaard
Publisher :
ISBN 13 :
Total Pages : 246 pages
Book Rating : 4.:/5 (876 download)
Download or read book Neural Networks for Modelling and Control of Dynamic Systems written by M. Norgaard and published by . This book was released on 2003 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Norgaard
Publisher :
ISBN 13 : 9788184893687
Total Pages : 260 pages
Book Rating : 4.8/5 (936 download)
Download or read book Neural Networks For Modelling And Control Of Dynamic Systems: A Practitioner'S Handbook written by Norgaard and published by . This book was released on 2009-09-01 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Juš Kocijan
Publisher : Springer
ISBN 13 : 3319210211
Total Pages : 281 pages
Book Rating : 4.3/5 (192 download)
Download or read book Modelling and Control of Dynamic Systems Using Gaussian Process Models written by Juš Kocijan and published by Springer. This book was released on 2015-11-21 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.
Author : Jorge D. Rios
Publisher : Academic Press
ISBN 13 : 0128170794
Total Pages : 160 pages
Book Rating : 4.1/5 (281 download)
Download or read book Neural Networks Modeling and Control written by Jorge D. Rios and published by Academic Press. This book was released on 2020-01-15 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on two methodologies: sliding mode control and Inverse Optimal Neural Control. As well as considering the different neural control models and complications that are associated with them, this book also analyzes potential applications, prototypes and future trends. Provide in-depth analysis of neural control models and methodologies Presents a comprehensive review of common problems in real-life neural network systems Includes an analysis of potential applications, prototypes and future trends
Author : Cornelius T. Leondes
Publisher :
ISBN 13 : 0124438679
Total Pages : 438 pages
Book Rating : 4.1/5 (244 download)
Download or read book Control and Dynamic Systems written by Cornelius T. Leondes and published by . This book was released on 1998 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book emphasizes neural network structures for achieving practical and effective systems, and provides many examples. Practitioners, researchers, and students in industrial, manufacturing, electrical, mechanical,and production engineering will find this volume a unique and comprehensive reference source for diverse application methodologies. Control and Dynamic Systems covers the important topics of highly effective Orthogonal Activation Function Based Neural Network System Architecture, multi-layer recurrent neural networks for synthesizing and implementing real-time linear control,adaptive control of unknown nonlinear dynamical systems, Optimal Tracking Neural Controller techniques, a consideration of unified approximation theory and applications, techniques for the determination of multi-variable nonlinear model structures for dynamic systems with a detailed treatment of relevant system model input determination, High Order Neural Networks and Recurrent High Order Neural Networks, High Order Moment Neural Array Systems, Online Learning Neural Network controllers, and Radial Bias Function techniques. Key Features Coverage includes: * Orthogonal Activation Function Based Neural Network System Architecture (OAFNN) * Multilayer recurrent neural networks for synthesizing and implementing real-time linear control * Adaptive control of unknown nonlinear dynamical systems * Optimal Tracking Neural Controller techniques * Consideration of unified approximation theory and applications * Techniques for determining multivariable nonlinear model structures for dynamic systems, with a detailed treatment of relevant system model input determination
Author : Zhang, Ming
Publisher : IGI Global
ISBN 13 : 1522500642
Total Pages : 538 pages
Book Rating : 4.5/5 (225 download)
Download or read book Applied Artificial Higher Order Neural Networks for Control and Recognition written by Zhang, Ming and published by IGI Global. This book was released on 2016-05-05 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, Higher Order Neural Networks (HONNs) have been widely adopted by researchers for applications in control signal generating, pattern recognition, nonlinear recognition, classification, and predition of control and recognition scenarios. Due to the fact that HONNs have been proven to be faster, more accurate, and easier to explain than traditional neural networks, their applications are limitless. Applied Artificial Higher Order Neural Networks for Control and Recognition explores the ways in which higher order neural networks are being integrated specifically for intelligent technology applications. Emphasizing emerging research, practice, and real-world implementation, this timely reference publication is an essential reference source for researchers, IT professionals, and graduate-level computer science and engineering students.
Author :
Publisher : Academic Press
ISBN 13 : 0080553907
Total Pages : 459 pages
Book Rating : 4.0/5 (85 download)
Download or read book Neural Network Systems Techniques and Applications written by and published by Academic Press. This book was released on 1998-02-09 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book emphasizes neural network structures for achieving practical and effective systems, and provides many examples. Practitioners, researchers, and students in industrial, manufacturing, electrical, mechanical,and production engineering will find this volume a unique and comprehensive reference source for diverse application methodologies. Control and Dynamic Systems covers the important topics of highly effective Orthogonal Activation Function Based Neural Network System Architecture, multi-layer recurrent neural networks for synthesizing and implementing real-time linear control,adaptive control of unknown nonlinear dynamical systems, Optimal Tracking Neural Controller techniques, a consideration of unified approximation theory and applications, techniques for the determination of multi-variable nonlinear model structures for dynamic systems with a detailed treatment of relevant system model input determination, High Order Neural Networks and Recurrent High Order Neural Networks, High Order Moment Neural Array Systems, Online Learning Neural Network controllers, and Radial Bias Function techniques. Coverage includes: Orthogonal Activation Function Based Neural Network System Architecture (OAFNN) Multilayer recurrent neural networks for synthesizing and implementing real-time linear control Adaptive control of unknown nonlinear dynamical systems Optimal Tracking Neural Controller techniques Consideration of unified approximation theory and applications Techniques for determining multivariable nonlinear model structures for dynamic systems, with a detailed treatment of relevant system model input determination
Author : Nancy Arana-Daniel
Publisher : CRC Press
ISBN 13 : 1351231774
Total Pages : 246 pages
Book Rating : 4.3/5 (512 download)
Download or read book Neural Networks for Robotics written by Nancy Arana-Daniel and published by CRC Press. This book was released on 2018-08-21 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book offers an insight on artificial neural networks for giving a robot a high level of autonomous tasks, such as navigation, cost mapping, object recognition, intelligent control of ground and aerial robots, and clustering, with real-time implementations. The reader will learn various methodologies that can be used to solve each stage on autonomous navigation for robots, from object recognition, clustering of obstacles, cost mapping of environments, path planning, and vision to low level control. These methodologies include real-life scenarios to implement a wide range of artificial neural network architectures.
Author : Konstantinos Diamantaras
Publisher : Springer Science & Business Media
ISBN 13 : 3642158242
Total Pages : 591 pages
Book Rating : 4.6/5 (421 download)
Download or read book Artificial Neural Networks - ICANN 2010 written by Konstantinos Diamantaras and published by Springer Science & Business Media. This book was released on 2010-09-03 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three volume set LNCS 6352, LNCS 6353, and LNCS 6354 constitutes the refereed proceedings of the 20th International Conference on Artificial Neural Networks, ICANN 2010, held in Thessaloniki, Greece, in September 20010. The 102 revised full papers, 68 short papers and 29 posters presented were carefully reviewed and selected from 241 submissions. The third volume is divided in topical sections on classification – pattern recognition, learning algorithms and systems, computational intelligence, IEM3 workshop, CVA workshop, and SOINN workshop.
Author : Zhang, Ming
Publisher : IGI Global
ISBN 13 : 1466621761
Total Pages : 455 pages
Book Rating : 4.4/5 (666 download)
Download or read book Artificial Higher Order Neural Networks for Modeling and Simulation written by Zhang, Ming and published by IGI Global. This book was released on 2012-10-31 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.
Author : Le Anh Tuan
Publisher : BoD – Books on Demand
ISBN 13 : 1789848261
Total Pages : 202 pages
Book Rating : 4.7/5 (898 download)
Download or read book Applied Modern Control written by Le Anh Tuan and published by BoD – Books on Demand. This book was released on 2019-02-13 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes recent studies on modern control systems using various control techniques. The control systems cover large complex systems such as train operation systems to micro systems in nanotechnology. Various control trends and techniques are discussed from practically modern approaches such as Internet of Things, artificial neural networks, machine learning to theoretical approaches such as zero-placement, bang-bang, optimal control, predictive control, and fuzzy approach.
Author : W. Thomas Miller
Publisher : MIT Press
ISBN 13 : 9780262631617
Total Pages : 548 pages
Book Rating : 4.6/5 (316 download)
Download or read book Neural Networks for Control written by W. Thomas Miller and published by MIT Press. This book was released on 1995 with total page 548 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Networks for Control brings together examples of all the most important paradigms for the application of neural networks to robotics and control. Primarily concerned with engineering problems and approaches to their solution through neurocomputing systems, the book is divided into three sections: general principles, motion control, and applications domains (with evaluations of the possible applications by experts in the applications areas.) Special emphasis is placed on designs based on optimization or reinforcement, which will become increasingly important as researchers address more complex engineering challenges or real biological-control problems.A Bradford Book. Neural Network Modeling and Connectionism series
Author : Kukatlapalli Pradeep Kumar
Publisher : John Wiley & Sons
ISBN 13 : 1119841976
Total Pages : 367 pages
Book Rating : 4.1/5 (198 download)
Download or read book Data Engineering and Data Science written by Kukatlapalli Pradeep Kumar and published by John Wiley & Sons. This book was released on 2023-08-29 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: DATA ENGINEERING and DATA SCIENCE Written and edited by one of the most prolific and well-known experts in the field and his team, this exciting new volume is the “one-stop shop” for the concepts and applications of data science and engineering for data scientists across many industries. The field of data science is incredibly broad, encompassing everything from cleaning data to deploying predictive models. However, it is rare for any single data scientist to be working across the spectrum day to day. Data scientists usually focus on a few areas and are complemented by a team of other scientists and analysts. Data engineering is also a broad field, but any individual data engineer doesn’t need to know the whole spectrum of skills. Data engineering is the aspect of data science that focuses on practical applications of data collection and analysis. For all the work that data scientists do to answer questions using large sets of information, there have to be mechanisms for collecting and validating that information. In this exciting new volume, the team of editors and contributors sketch the broad outlines of data engineering, then walk through more specific descriptions that illustrate specific data engineering roles. Data-driven discovery is revolutionizing the modeling, prediction, and control of complex systems. This book brings together machine learning, engineering mathematics, and mathematical physics to integrate modeling and control of dynamical systems with modern methods in data science. It highlights many of the recent advances in scientific computing that enable data-driven methods to be applied to a diverse range of complex systems, such as turbulence, the brain, climate, epidemiology, finance, robotics, and autonomy. Whether for the veteran engineer or scientist working in the field or laboratory, or the student or academic, this is a must-have for any library.
Author : Michael Berthold
Publisher : Springer Science & Business Media
ISBN 13 : 3540408134
Total Pages : 638 pages
Book Rating : 4.5/5 (44 download)
Download or read book Advances in Intelligent Data Analysis V written by Michael Berthold and published by Springer Science & Business Media. This book was released on 2003-08-21 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 5th International Conference on Intelligent Data Analysis, IDA 2003, held in Berlin, Germany in August 2003. The 56 revised papers presented were carefully reviewed and selected from 180 submissions. The papers are organized in topical sections on machine learning, probability and topology, classification and pattern recognition, clustering, applications, modeling, and data processing.
Author : Johan A.K. Suykens
Publisher : Springer Science & Business Media
ISBN 13 : 1475724934
Total Pages : 242 pages
Book Rating : 4.4/5 (757 download)
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.
Author : Hamid Asgari
Publisher : CRC Press
ISBN 13 : 1498726631
Total Pages : 214 pages
Book Rating : 4.4/5 (987 download)
Download or read book Gas Turbines Modeling, Simulation, and Control written by Hamid Asgari and published by CRC Press. This book was released on 2015-10-16 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gas Turbines Modeling, Simulation, and Control: Using Artificial Neural Networks provides new approaches and novel solutions to the modeling, simulation, and control of gas turbines (GTs) using artificial neural networks (ANNs). After delivering a brief introduction to GT performance and classification, the book:Outlines important criteria to consi
Author : Józef Korbicz
Publisher : Springer Science & Business Media
ISBN 13 : 3642186157
Total Pages : 936 pages
Book Rating : 4.6/5 (421 download)
Download or read book Fault Diagnosis written by Józef Korbicz and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 936 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive work presents the status and likely development of fault diagnosis, an emerging discipline of modern control engineering. It covers fundamentals of model-based fault diagnosis in a wide context, providing a good introduction to the theoretical foundation and many basic approaches of fault detection.
