Adaptive Control With Recurrent High Order Neural Networks
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Adaptive Control With Recurrent High Order Neural Networks
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Author : George A. Rovithakis
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Adaptive Control With Recurrent High Order Neural Networks written by George A. Rovithakis and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Neural networks is one of those areas where an initial burst of enthusiasm and optimism leads to an explosion of papers in the journals and many presentations at conferences but it is only in the last decade that significant theoretical work on stability, convergence and robustness for the use of neural networks in control systems has been tackled. George Rovithakis and Manolis Christodoulou have been interested in these theoretical problems and in the practical aspects of neural network applications to industrial problems. This very welcome addition to the Advances in Industrial Control series provides a succinct report of their research. The neural network model at the core of their work is the Recurrent High Order Neural Network (RHONN) and a complete theoretical and simulation development is presented. Different readers will find different aspects of the development of interest. The last chapter of the monograph discusses the problem of manufacturing or production process scheduling.
Applied Artificial Higher Order Neural Networks For Control And Recognition
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Author : Zhang, Ming
language : en
Publisher: IGI Global
Release Date : 2016-05-05
Applied Artificial Higher Order Neural Networks For Control And Recognition written by Zhang, Ming and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-05-05 with Computers categories.
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.
Artificial Higher Order Neural Networks For Computer Science And Engineering Trends For Emerging Applications
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Author : Zhang, Ming
language : en
Publisher: IGI Global
Release Date : 2010-02-28
Artificial Higher Order Neural Networks For Computer Science And Engineering Trends For Emerging Applications written by Zhang, Ming and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-02-28 with Computers categories.
"This book introduces and explains Higher Order Neural Networks (HONNs) to people working in the fields of computer science and computer engineering, and how to use HONNS in these areas"--Provided by publisher.
Artificial Higher Order Neural Networks For Modeling And Simulation
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Author : Zhang, Ming
language : en
Publisher: IGI Global
Release Date : 2012-10-31
Artificial Higher Order Neural Networks For Modeling And Simulation written by Zhang, Ming and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-31 with Computers categories.
"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.
Discrete Time High Order Neural Control
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Author : Edgar N. Sanchez
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-04-29
Discrete Time High Order Neural Control written by Edgar N. Sanchez and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-29 with Mathematics categories.
Neural networks have become a well-established methodology as exempli?ed by their applications to identi?cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o?ers a better suited tool to model and control of nonlinear systems. There exist di?erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a viable alternative, new training algorithms, for example, those based on Kalman ?ltering, have been proposed. There already exists publications about trajectory tracking using neural networks; however, most of those works were developed for continuous-time systems. On the other hand, while extensive literature is available for linear discrete-timecontrolsystem,nonlineardiscrete-timecontroldesigntechniques have not been discussed to the same degree. Besides, discrete-time neural networks are better ?tted for real-time implementations.
Discrete Time High Order Neural Control
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Author : Edgar N. Sanchez
language : en
Publisher: Springer
Release Date : 2008-06-24
Discrete Time High Order Neural Control written by Edgar N. Sanchez and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-24 with Technology & Engineering categories.
Neural networks have become a well-established methodology as exempli?ed by their applications to identi?cation and control of general nonlinear and complex systems; the use of high order neural networks for modeling and learning has recently increased. Usingneuralnetworks,controlalgorithmscanbedevelopedtoberobustto uncertainties and modeling errors. The most used NN structures are Feedf- ward networks and Recurrent networks. The latter type o?ers a better suited tool to model and control of nonlinear systems. There exist di?erent training algorithms for neural networks, which, h- ever, normally encounter some technical problems such as local minima, slow learning, and high sensitivity to initial conditions, among others. As a viable alternative, new training algorithms, for example, those based on Kalman ?ltering, have been proposed. There already exists publications about trajectory tracking using neural networks; however, most of those works were developed for continuous-time systems. On the other hand, while extensive literature is available for linear discrete-timecontrolsystem,nonlineardiscrete-timecontroldesigntechniques have not been discussed to the same degree. Besides, discrete-time neural networks are better ?tted for real-time implementations.
Artificial Higher Order Neural Networks For Economics And Business
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Author : Zhang, Ming
language : en
Publisher: IGI Global
Release Date : 2008-07-31
Artificial Higher Order Neural Networks For Economics And Business written by Zhang, Ming and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-07-31 with Computers categories.
"This book is the first book to provide opportunities for millions working in economics, accounting, finance and other business areas education on HONNs, the ease of their usage, and directions on how to obtain more accurate application results. It provides significant, informative advancements in the subject and introduces the HONN group models and adaptive HONNs"--Provided by publisher.
System Identification And Adaptive Control
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Author : Yiannis Boutalis
language : en
Publisher: Springer Science & Business
Release Date : 2014-04-23
System Identification And Adaptive Control written by Yiannis Boutalis and has been published by Springer Science & Business this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-23 with Technology & Engineering categories.
Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.
Neural Networks For Robotics
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Author : Nancy Arana-Daniel
language : en
Publisher: CRC Press
Release Date : 2018-08-21
Neural Networks For Robotics written by Nancy Arana-Daniel and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-21 with Technology & Engineering categories.
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.
Artificial Neural Networks For Engineering Applications
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Author : Alma Y Alanis
language : en
Publisher: Academic Press
Release Date : 2019-02-13
Artificial Neural Networks For Engineering Applications written by Alma Y Alanis and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-13 with Science categories.
Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications.