Neural Systems for Control - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Systems for Control write by Omid Omidvar. This book was released on 1997-02-24. Neural Systems for Control available in PDF, EPUB and Kindle. 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
Neural Networks for Control
Neural Networks for Control - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Networks for Control write by W. Thomas Miller. This book was released on 1995. Neural Networks for Control available in PDF, EPUB and Kindle. Neural Networks for Control brings together examples of all the most important paradigms for the application of neural networks to robotics and control. Primarily concerned with engineering problems and approaches to their solution through neurocomputing systems, the book is divided into three sections: general principles, motion control, and applications domains (with evaluations of the possible applications by experts in the applications areas.) Special emphasis is placed on designs based on optimization or reinforcement, which will become increasingly important as researchers address more complex engineering challenges or real biological-control problems.A Bradford Book. Neural Network Modeling and Connectionism series
Artificial Neural Networks for Modelling and Control of Non-Linear Systems
Artificial Neural Networks for Modelling and Control of Non-Linear Systems - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Artificial Neural Networks for Modelling and Control of Non-Linear Systems write by Johan A.K. Suykens. This book was released on 2012-12-06. Artificial Neural Networks for Modelling and Control of Non-Linear Systems available in PDF, EPUB and Kindle. Artificial neural networks possess several properties that make them particularly attractive for applications to modelling and control of complex non-linear systems. Among these properties are their universal approximation ability, their parallel network structure and the availability of on- and off-line learning methods for the interconnection weights. However, dynamic models that contain neural network architectures might be highly non-linear and difficult to analyse as a result. Artificial Neural Networks for Modelling and Control of Non-Linear Systems investigates the subject from a system theoretical point of view. However the mathematical theory that is required from the reader is limited to matrix calculus, basic analysis, differential equations and basic linear system theory. No preliminary knowledge of neural networks is explicitly required. The book presents both classical and novel network architectures and learning algorithms for modelling and control. Topics include non-linear system identification, neural optimal control, top-down model based neural control design and stability analysis of neural control systems. A major contribution of this book is to introduce NLq Theory as an extension towards modern control theory, in order to analyze and synthesize non-linear systems that contain linear together with static non-linear operators that satisfy a sector condition: neural state space control systems are an example. Moreover, it turns out that NLq Theory is unifying with respect to many problems arising in neural networks, systems and control. Examples show that complex non-linear systems can be modelled and controlled within NLq theory, including mastering chaos. The didactic flavor of this book makes it suitable for use as a text for a course on Neural Networks. In addition, researchers and designers will find many important new techniques, in particular NLq emTheory, that have applications in control theory, system theory, circuit theory and Time Series Analysis.
Adaptive Control with Recurrent High-order Neural Networks
Adaptive Control with Recurrent High-order Neural Networks - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Adaptive Control with Recurrent High-order Neural Networks write by George A. Rovithakis. This book was released on 2012-12-06. Adaptive Control with Recurrent High-order Neural Networks available in PDF, EPUB and Kindle. 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.
Neural Systems for Control
Neural Systems for Control - read free eBook in online reader or directly download on the web page. Select files or add your book in reader. Download and read online ebook Neural Systems for Control write by Omid Omidvar. This book was released on 1997. Neural Systems for Control available in PDF, EPUB and Kindle. "Neutral Systems for Control" represents the most up-to-date developments in the rapidly growing application area of neural networks and focuses on research in natural and artificial neural systems directly applicable to control or making use of modern control theory. All researchers and students dealing with control systems will find the book of immense interest and assistance.
