Download or read book Applications of Neural Adaptive Control Technology written by Jens Kalkkuhl and published by World Scientific. This book was released on 1997 with total page 328 pages. 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.

Download or read book Adaptive Control with Recurrent High order Neural Networks written by George A. Rovithakis and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Neural Adaptive Control Technology written by Rafa? ?bikowski and published by World Scientific. This book was released on 1996 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Stable Adaptive Neural Network Control written by S.S. Ge and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 296 pages. 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.

Download or read book Applications of Neural Networks to Adaptive Control written by Russell W Scott (II.) and published by . This book was released on 1989 with total page 117 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount of a priori knowledge required to design some modern control systems is becoming prohibitive. Two current methods addressing this problem are robust control, in which the control design is insensitive to errors in system knowledge, and adaptive control, in which the control law is adjusted in response to a continually updated model of the system. This thesis examines the application of parallel distributed processing (neural networks) to the problem of adaptive control. The structure of neural networks is introduced, focusing on the Backpropagation paradigm. A general form of controller consistent with use in neural networks is developed and combined with a discussion of linear east squares parameter estimation techniques to suggest a structure for neural network adaptive controllers. This neural network adaptive control structure is then applied to a number of estimation and control problems using as a model the longitudinal motion of the A-4 aircraft. The purpose of this thesis is to develop and demonstrate a neural network adaptive control structure consistent with adaptive control theory. Theses. (RH).

Download or read book Intelligent Adaptive Control written by Lakhmi C. Jain and published by CRC Press. This book was released on 1998-12-29 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes important techniques, developments, and applications of computational intelligence in system control. Chapters present: an introduction to the fundamentals of neural networks, fuzzy logic, and evolutionary computing a rigorous treatment of intelligent control industrial applications of intelligent control and soft computing, including transportation, petroleum, motor drive, industrial automation, and fish processing other knowledge-based techniques, including vehicle driving aid and air traffic management Intelligent Adaptive Control provides a state-of-the-art treatment of practical applications of computational intelligence in system control. The book cohesively covers introductory and advanced theory, design, implementation, and industrial use - serving as a singular resource for the theory and application of intelligent control, particularly employing fuzzy logic, neural networks, and evolutionary computing.

Download or read book Neural Systems for Control written by Omid Omidvar and published by Elsevier. This book was released on 1997-02-24 with total page 375 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Neural Network Applications in Control written by George William Irwin and published by IET. This book was released on 1995 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Adaptive Control written by Dianwei Qian and published by . This book was released on 2018-03 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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--

Download or read book Applications of Neural Networks to Adaptive Control written by Russell W. Scott and published by . This book was released on 1989 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Applications of Neural Networks to Adaptive Control written by Russell W. Scott and published by . This book was released on 1989 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Research in Neural Network Based Robust Adaptive Control with Application to Alternate Control Technology Missile Autopilot Design written by Anthony J. Calise and published by . This book was released on 1995 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Neural Network Based Adaptive Control and Its Applications to Aerial Vehicles written by Seungjae Lee and published by . This book was released on 2001 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Evolutionary Learning Algorithms for Neural Adaptive Control written by Dimitris C. Dracopoulos and published by Springer. This book was released on 1997-08-15 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: After an introduction to neural networks and genetic algorithms, this volume describes in detail how neural networks and evolutionary techniques (specifically genetic algorithms and genetic programming) can be applied to the adaptive control of complex dynamic systems (including chaotic ones). A number of examples are presented and useful tips are given for the application of the techniques described. The fundamentals of dynamic systems theory and classical adaptive control are also given. This volume will be of particular interest to undergraduate and postgraduate students taking courses in neural networks, genetic algorithms or control systems, researchers in neural networks and genetic algorithms who need to extend their field of application to dynamic systems and control, and control theorists/professionals who would like to use these advanced learning techniques for solving high-nonlinear control theory problems.

Download or read book Techniques for Adaptive Control written by Vance VanDoren and published by Elsevier. This book was released on 2002-10-31 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Techniques for Adaptive Control compiles chapters from a team of expert contributors that allow readers to gain a perspective into a number of different approaches to adaptive control. In order to do this, each contributor provides an overview of a particular product, how it works, and reasons why a user would want it as well as an in depth explanation of their particular method.This is one of the latest technologies to emerge in the instrumentation and control field. These latest control methodologies offer a means to revolutionize plant and process efficiency, response time and profitability by allowing a process to be regulated by a form of rule-based AI, without human intervention.Rather than the common academic-based approach that books on this subject generally take, the contributions here outline practical applications of adaptive control technology allowing for a real look inside the industry and the new technologies available. * Written by a team of contributors from the industry's best-known product manufacturers and software developers* Provides real insight into new technologies available in the industry* Outlines practical applications of adaptive control technology

Download or read book Applications of Neural Networks in High Assurance Systems written by Johann M.Ph. Schumann and published by Springer Science & Business Media. This book was released on 2010-02-28 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Applications of Neural Networks in High Assurance Systems" is the first book directly addressing a key part of neural network technology: methods used to pass the tough verification and validation (V&V) standards required in many safety-critical applications. The book presents what kinds of evaluation methods have been developed across many sectors, and how to pass the tests. A new adaptive structure of V&V is developed in this book, different from the simple six sigma methods usually used for large-scale systems and different from the theorem-based approach used for simplified component subsystems.

Download or read book Safety Reliability and Applications of Emerging Intelligent Control Technologies written by T.S. Ng and published by Elsevier. This book was released on 2014-06-28 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasingly, over the last few years, intelligent controllers have been incorporated into control systems. Presently, the numbers and types of intelligent controllers that contain variations of fuzzy logic, neural network, genetic algorithms or some other forms of knowledge based reasoning technology are dramatically rising. However, considering the stability of the system, when such controllers are included it is difficult to analyse and predict system behaviour under unexpected conditions. Leading researchers and industrial practitioners were able to discuss and evaluate current development and future research directions at the first IFAC International Workshop on safety, reliability and applications on emerging intelligent control technology. This publication contains the papers, covering a wide range of topics, presented at the workshop.