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Author: Jens Kalkkuhl
Publisher: World Scientific
ISBN: 9789810231514
Category : Technology & Engineering
Languages : en
Pages : 328
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Book Description
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.
Author: Jens Kalkkuhl
Publisher: World Scientific
ISBN: 9789810231514
Category : Technology & Engineering
Languages : en
Pages : 328
Get Book Here
Book Description
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.
Author: George A. Rovithakis
Publisher: Springer Science & Business Media
ISBN: 1447107853
Category : Computers
Languages : en
Pages : 203
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Book Description
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.
Author: Rafa? ?bikowski
Publisher: World Scientific
ISBN: 9789810225575
Category : Technology & Engineering
Languages : en
Pages : 368
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Book Description
This book is an outgrowth of the workshop on Neural Adaptive Control Technology, NACT I, held in 1995 in Glasgow. Selected workshop participants were asked to substantially expand and revise their contributions to make them into full papers.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). A major aim of the NACT project 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 Daimler-Benz.In the book emphasis is put on development of sound theory of neural adaptive control for nonlinear control systems, but firmly anchored in the engineering context of industrial practice. Therefore the contributors are both renowned academics and practitioners from major industrial users of neurocontrol.
Author: S.S. Ge
Publisher: Springer Science & Business Media
ISBN: 1475765770
Category : Science
Languages : en
Pages : 296
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Book Description
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.
Author: George William Irwin
Publisher: IET
ISBN: 9780852968529
Category : Computers
Languages : en
Pages : 320
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Book Description
The aim is to present an introduction to, and an overview of, the present state of neural network research and development, with an emphasis on control systems application studies. The book is useful to a range of levels of reader. The earlier chapters introduce the more popular networks and the fundamental control principles, these are followed by a series of application studies, most of which are industrially based, and the book concludes with a consideration of some recent research.
Author: Omid Omidvar
Publisher: Elsevier
ISBN: 0080537391
Category : Computers
Languages : en
Pages : 375
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Book Description
Control problems offer an industrially important application and a guide to understanding control systems for those working in Neural Networks. Neural Systems for Control represents the most up-to-date developments in the rapidly growing aplication area of neural networks and focuses on research in natural and artifical neural systems directly applicable to control or making use of modern control theory. The book covers such important new developments in control systems such as intelligent sensors in semiconductor wafer manufacturing; the relation between muscles and cerebral neurons in speech recognition; online compensation of reconfigurable control for spacecraft aircraft and other systems; applications to rolling mills, robotics and process control; the usage of past output data to identify nonlinear systems by neural networks; neural approximate optimal control; model-free nonlinear control; and neural control based on a regulation of physiological investigation/blood pressure control. All researchers and students dealing with control systems will find the fascinating Neural Systems for Control of immense interest and assistance. - Focuses on research in natural and artifical neural systems directly applicable to contol or making use of modern control theory - Represents the most up-to-date developments in this rapidly growing application area of neural networks - Takes a new and novel approach to system identification and synthesis
Author: Dianwei Qian
Publisher:
ISBN: 9781536131185
Category : Adaptive control systems
Languages : en
Pages : 233
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Book Description
Adaptive control is the control method used by a controller which must adapt to a controlled system with parameters which vary, or are initially uncertain. An adaptive control system utilizes on-line identification of which either system parameter or controller parameter, which does not need a priori information about the bounds on these uncertain or time-varying parameters. These approaches consider their control design in the sense of Lyapunov. Besides, there are still some branches by combining adaptive control and other control methods, i.e., nonlinear control methods, intelligent control methods, and predict control methods, to name but a few. Addresses some original contributions reporting the latest advances in adaptive control. It aims to gather the latest research on state-of-the-art methods, applications and research for the adaptive control theory, and recent new findings obtained by the technique of adaptive control. Apparently, the book cannot include all research topics. Different aspects of adaptive control are explored. Chapters includes some new tendencies and developments in research on a adaptive formation controller for multi-robot systems; L1 adaptive control design of the the longitudinal dynamics of a hypersonic vehicle model; adaptive high-gain control of biologically inspired receptor systems; adaptive residual vibration suppression of sigid-flexible coupled systems; neuro-hierarchical sliding mode control for under-actuated mechanical systems; neural network adaptive PID control design based on PLC for a water-level system; and fuzzy-based design of networked control systems with random time delays and packet dropout in the forward communication channel--
Author: Yang Li
Publisher: Academic Press
ISBN: 0128154322
Category : Technology & Engineering
Languages : en
Pages : 190
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Book Description
Adaptive Sliding Mode Neural Network Control for Nonlinear Systems introduces nonlinear systems basic knowledge, analysis and control methods, and applications in various fields. It offers instructive examples and simulations, along with the source codes, and provides the basic architecture of control science and engineering. - Introduces nonlinear systems' basic knowledge, analysis and control methods, along with applications in various fields - Offers instructive examples and simulations, including source codes - Provides the basic architecture of control science and engineering
Author:
Publisher:
ISBN:
Category : Naval research
Languages : en
Pages : 176
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Book Description
Author: M A Hussain
Publisher: World Scientific
ISBN: 178326148X
Category : Computers
Languages : en
Pages : 423
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Book Description
This book is a follow-up to the IChemE symposium on “Neural Networks and Other Learning Technologies”, held at Imperial College, UK, in May 1999. The interest shown by the participants, especially those from the industry, has been instrumental in producing the book. The papers have been written by contributors of the symposium and experts in this field from around the world. They present all the important aspects of neural network utilisation as well as show the versatility of neural networks in various aspects of process engineering problems — modelling, estimation, control, optimisation and industrial applications.
