Stable Adaptive Control Of Unknown Nonlinear Dynamic Systems Using Neural Networks
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Stable Adaptive Control Of Unknown Nonlinear Dynamic Systems Using Neural Networks
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Author : Olawale Adetona
language : en
Publisher:
Release Date : 1998
Stable Adaptive Control Of Unknown Nonlinear Dynamic Systems Using Neural Networks written by Olawale Adetona and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Adaptive control systems categories.
Stable Adaptive Control And Estimation For Nonlinear Systems
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Author : Jeffrey T. Spooner
language : en
Publisher: John Wiley & Sons
Release Date : 2004-04-07
Stable Adaptive Control And Estimation For Nonlinear Systems written by Jeffrey T. Spooner and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-04-07 with Science categories.
Thema dieses Buches ist die Anwendung neuronaler Netze und Fuzzy-Logic-Methoden zur Identifikation und Steuerung nichtlinear-dynamischer Systeme. Dabei werden fortgeschrittene Konzepte der herkömmlichen Steuerungstheorie mit den intuitiven Eigenschaften intelligenter Systeme kombiniert, um praxisrelevante Steuerungsaufgaben zu lösen. Die Autoren bieten viel Hintergrundmaterial; ausgearbeitete Beispiele und Übungsaufgaben helfen Studenten und Praktikern beim Vertiefen des Stoffes. Lösungen zu den Aufgaben sowie MATLAB-Codebeispiele sind ebenfalls enthalten.
Neural Network Systems Techniques And Applications
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Author :
language : en
Publisher: Academic Press
Release Date : 1998-02-09
Neural Network Systems Techniques And Applications written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998-02-09 with Computers categories.
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
Control And Dynamic Systems
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Author : Cornelius T. Leondes
language : en
Publisher:
Release Date : 1998
Control And Dynamic Systems written by Cornelius T. Leondes and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computers categories.
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
Adaptive Control Of Nonsmooth Dynamic Systems
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Author : Gang Tao
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17
Adaptive Control Of Nonsmooth Dynamic Systems written by Gang Tao 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 2013-04-17 with Technology & Engineering categories.
Many of the non-smooth, non-linear phenomena covered in this well-balanced book are of vital importance in almost any field of engineering. Contributors from all over the world ensure that no one area’s slant on the subjects predominates.
Adaptive Control Of Unknown Dynamic Systems Using Neural Networks
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Author : Kyungmoon Nho
language : en
Publisher:
Release Date : 1996
Adaptive Control Of Unknown Dynamic Systems Using Neural Networks written by Kyungmoon Nho and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Adaptive control systems categories.
Applications Of Neural Adaptive Control Technology
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Author : Andrzej Dzielinski
language : en
Publisher: World Scientific
Release Date : 1997-09-02
Applications Of Neural Adaptive Control Technology written by Andrzej Dzielinski and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-09-02 with Computers categories.
This book presents the results of the second workshop on Neural Adaptive Control Technology, NACT II, held on September 9-10, 1996, in Berlin. The workshop was organised in connection with a three-year European-Union-funded Basic Research Project in the ESPRIT framework, called NACT, a collaboration between Daimler-Benz (Germany) and the University of Glasgow (Scotland).The NACT project, which began on 1 April 1994, is a study of the fundamental properties of neural-network-based adaptive control systems. Where possible, links with traditional adaptive control systems are exploited. A major aim is to develop a systematic engineering procedure for designing neural controllers for nonlinear dynamic systems. The techniques developed are being evaluated on concrete industrial problems from within the Daimler-Benz group of companies.The aim of the workshop was to bring together selected invited specialists in the fields of adaptive control, nonlinear systems and neural networks. The first workshop (NACT I) took place in Glasgow in May 1995 and was mainly devoted to theoretical issues of neural adaptive control. Besides monitoring further development of theory, the NACT II workshop was focused on industrial applications and software tools. This context dictated the focus of the book and guided the editors in the choice of the papers and their subsequent reshaping into substantive book chapters. Thus, with the project having progressed into its applications stage, emphasis is put on the transfer of theory of neural adaptive engineering into industrial practice. The contributors are therefore both renowned academics and practitioners from major industrial users of neurocontrol.
Differential Neural Networks For Robust Nonlinear Control
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Author : Alexander S. Poznyak
language : en
Publisher: World Scientific
Release Date : 2001
Differential Neural Networks For Robust Nonlinear Control written by Alexander S. Poznyak and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Science categories.
This book deals with continuous time dynamic neural networks theory applied to the solution of basic problems in robust control theory, including identification, state space estimation (based on neuro-observers) and trajectory tracking. The plants to be identified and controlled are assumed to be a priori unknown but belonging to a given class containing internal unmodelled dynamics and external perturbations as well. The error stability analysis and the corresponding error bounds for different problems are presented. The effectiveness of the suggested approach is illustrated by its application to various controlled physical systems (robotic, chaotic, chemical, etc.). Contents: Theoretical Study: Neural Networks Structures; Nonlinear System Identification: Differential Learning; Sliding Mode Identification: Algebraic Learning; Neural State Estimation; Passivation via Neuro Control; Neuro Trajectory Tracking; Neurocontrol Applications: Neural Control for Chaos; Neuro Control for Robot Manipulators; Identification of Chemical Processes; Neuro Control for Distillation Column; General Conclusions and Future Work; Appendices: Some Useful Mathematical Facts; Elements of Qualitative Theory of ODE; Locally Optimal Control and Optimization. Readership: Graduate students, researchers, academics/lecturers and industrialists in neural networks.
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.
Control And Dynamic Systems V53 High Performance Systems Techniques And Applications
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Author : C.T. Leonides
language : en
Publisher: Elsevier
Release Date : 2012-12-02
Control And Dynamic Systems V53 High Performance Systems Techniques And Applications written by C.T. Leonides and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-02 with Technology & Engineering categories.
Control and Dynamic Systems: Advances in Theory and Applications, Volume 53: High Performance Systems Techniques and Applications covers the significant research works on the issues and applications of high performance control systems techniques. This book is divided into 11 chapters and starts with an examination of the contribution of computing power with advances in theory in global optimization. The next chapters present robust solution techniques for combined filtering and parameter estimation in discrete time and the design and analysis of model reference adaptive control techniques for both continuous and discrete time multivariable plants with additive and multiplicative unmodeled dynamics. These topics are followed by discussions of the decentralized adaptive control; robust recursive estimation of states and parameters of bilinear systems; the design of robust control systems under uncertainty cases; and the techniques for state estimation for linear stationary dynamic systems that are subject to unknown time varying plant and output disturbances. Other chapters deal with the sliding control algorithm, the techniques in robust broadband beamforming, and the different categories of robust robotic controllers. The final chapter looks into the problems and issues of performance and versatility of non-linear control and the application of artificial neural networks. This book is of great value to process, control, mechanical, and design engineers.