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Stable Adaptive Neural Network Control

2013-03-09 Science
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Release : 2013-03-09
Genre : Science
Kind : eBook
Book Rating : 770/5 ( reviews)

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Book Synopsis Stable Adaptive Neural Network Control by : S.S. Ge

Download or read book Stable Adaptive Neural Network Control written by S.S. Ge. This book was released on 2013-03-09. Available in PDF, EPUB and Kindle. Book excerpt: Recent years have seen a rapid development of neural network control tech niques and their successful applications. Numerous simulation studies and actual industrial implementations show that artificial neural network is a good candidate for function approximation and control system design in solving the control problems of complex nonlinear systems in the presence of different kinds of uncertainties. Many control approaches/methods, reporting inventions and control applications within the fields of adaptive control, neural control and fuzzy systems, have been published in various books, journals and conference proceedings. In spite of these remarkable advances in neural control field, due to the complexity of nonlinear systems, the present research on adaptive neural control is still focused on the development of fundamental methodologies. From a theoretical viewpoint, there is, in general, lack of a firmly mathematical basis in stability, robustness, and performance analysis of neural network adaptive control systems. This book is motivated by the need for systematic design approaches for stable adaptive control using approximation-based techniques. The main objec tives of the book are to develop stable adaptive neural control strategies, and to perform transient performance analysis of the resulted neural control systems analytically. Other linear-in-the-parameter function approximators can replace the linear-in-the-parameter neural networks in the controllers presented in the book without any difficulty, which include polynomials, splines, fuzzy systems, wavelet networks, among others. Stability is one of the most important issues being concerned if an adaptive neural network controller is to be used in practical applications.

Stable Adaptive Control and Estimation for Nonlinear Systems

2004-04-07 Science
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Release : 2004-04-07
Genre : Science
Kind : eBook
Book Rating : 974/5 ( reviews)

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Book Synopsis Stable Adaptive Control and Estimation for Nonlinear Systems by : Jeffrey T. Spooner

Download or read book Stable Adaptive Control and Estimation for Nonlinear Systems written by Jeffrey T. Spooner. This book was released on 2004-04-07. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Applications of Neural Adaptive Control Technology

1997 Technology & Engineering
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Release : 1997
Genre : Technology & Engineering
Kind : eBook
Book Rating : 514/5 ( reviews)

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Book Synopsis Applications of Neural Adaptive Control Technology by : Jens Kalkkuhl

Download or read book Applications of Neural Adaptive Control Technology written by Jens Kalkkuhl. This book was released on 1997. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Adaptive Neural Network Control Of Robotic Manipulators

1998-12-04 Technology & Engineering
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Release : 1998-12-04
Genre : Technology & Engineering
Kind : eBook
Book Rating : 227/5 ( reviews)

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Book Synopsis Adaptive Neural Network Control Of Robotic Manipulators by : Sam Shuzhi Ge

Download or read book Adaptive Neural Network Control Of Robotic Manipulators written by Sam Shuzhi Ge. This book was released on 1998-12-04. Available in PDF, EPUB and Kindle. Book excerpt: Recently, there has been considerable research interest in neural network control of robots, and satisfactory results have been obtained in solving some of the special issues associated with the problems of robot control in an “on-and-off” fashion. This book is dedicated to issues on adaptive control of robots based on neural networks. The text has been carefully tailored to (i) give a comprehensive study of robot dynamics, (ii) present structured network models for robots, and (iii) provide systematic approaches for neural network based adaptive controller design for rigid robots, flexible joint robots, and robots in constraint motion. Rigorous proof of the stability properties of adaptive neural network controllers is provided. Simulation examples are also presented to verify the effectiveness of the controllers, and practical implementation issues associated with the controllers are also discussed.

Radial Basis Function (RBF) Neural Network Control for Mechanical Systems

2013-01-26 Technology & Engineering
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Release : 2013-01-26
Genre : Technology & Engineering
Kind : eBook
Book Rating : 165/5 ( reviews)

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Book Synopsis Radial Basis Function (RBF) Neural Network Control for Mechanical Systems by : Jinkun Liu

Download or read book Radial Basis Function (RBF) Neural Network Control for Mechanical Systems written by Jinkun Liu. This book was released on 2013-01-26. Available in PDF, EPUB and Kindle. Book excerpt: Radial Basis Function (RBF) Neural Network Control for Mechanical Systems is motivated by the need for systematic design approaches to stable adaptive control system design using neural network approximation-based techniques. The main objectives of the book are to introduce the concrete design methods and MATLAB simulation of stable adaptive RBF neural control strategies. In this book, a broad range of implementable neural network control design methods for mechanical systems are presented, such as robot manipulators, inverted pendulums, single link flexible joint robots, motors, etc. Advanced neural network controller design methods and their stability analysis are explored. The book provides readers with the fundamentals of neural network control system design. This book is intended for the researchers in the fields of neural adaptive control, mechanical systems, Matlab simulation, engineering design, robotics and automation. Jinkun Liu is a professor at Beijing University of Aeronautics and Astronautics.

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