Neural Fuzzy Control Systems With Structure Parameter Learning
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Author | : Chin-teng Lin |
Publisher | : World Scientific Publishing Company |
Total Pages | : 152 |
Release | : 1994-02-08 |
Genre | : Technology & Engineering |
ISBN | : 9813104708 |
A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.
Author | : Ching Tai Lin |
Publisher | : |
Total Pages | : 127 |
Release | : 1994 |
Genre | : |
ISBN | : 9789814354240 |
Author | : C. T. Lin |
Publisher | : World Scientific |
Total Pages | : 150 |
Release | : 1994 |
Genre | : Computers |
ISBN | : 9789810216139 |
A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.
Author | : Ching Tai Lin |
Publisher | : Prentice Hall |
Total Pages | : 824 |
Release | : 1996 |
Genre | : Computers |
ISBN | : |
Neural Fuzzy Systems provides a comprehensive, up-to-date introduction to the basic theories of fuzzy systems and neural networks, as well as an exploration of how these two fields can be integrated to create Neural-Fuzzy Systems. It includes Matlab software, with a Neural Network Toolkit, and a Fuzzy System Toolkit.
Author | : David A. White |
Publisher | : Van Nostrand Reinhold Company |
Total Pages | : 600 |
Release | : 1992 |
Genre | : Technology & Engineering |
ISBN | : |
This handbook shows the reader how to develop neural networks and apply them to various engineering control problems. Based on a workshop on aerospace applications, this tutorial covers integration of neural networks with existing control architectures as well as new neurocontrol architectures in nonlinear control.
Author | : Leszek Rutkowski |
Publisher | : Springer Science & Business Media |
Total Pages | : 286 |
Release | : 2006-04-18 |
Genre | : Computers |
ISBN | : 1402080433 |
Flexible Neuro-Fuzzy Systems is the first professional literature about the new class of powerful, flexible fuzzy systems. The author incorporates various flexibility parameters to the construction of neuro-fuzzy systems. This approach dramatically improves their performance, allowing the systems to perfectly represent the pattern encoded in data. Flexible Neuro-Fuzzy Systems is the only book that proposes a flexible approach to fuzzy modeling and fills the gap in existing literature. This book introduces new fuzzy systems which outperform previous approaches to system modeling and classification, and has the following features: -Provides a framework for unification, construction and development of neuro-fuzzy systems; -Presents complete algorithms in a systematic and structured fashion, facilitating understanding and implementation, -Covers not only advanced topics but also fundamentals of fuzzy sets, -Includes problems and exercises following each chapter, -Illustrates the results on a wide variety of simulations, -Provides tools for possible applications in business and economics, medicine and bioengineering, automatic control, robotics and civil engineering.
Author | : Junhong Nie |
Publisher | : Prentice Hall PTR |
Total Pages | : 262 |
Release | : 1995 |
Genre | : Computers |
ISBN | : |
Illustrating how fuzzy logic and neural networks can be integrated into a model reference control context for real-time control of multivariable systems, this book provides an architecture which accommodates several popular learning/reasoning paradigms.
Author | : Abraham Kandel |
Publisher | : CRC Press |
Total Pages | : 664 |
Release | : 1993-09-27 |
Genre | : Computers |
ISBN | : 9780849344961 |
Fuzzy Control Systems explores one of the most active areas of research involving fuzzy set theory. The contributors address basic issues concerning the analysis, design, and application of fuzzy control systems. Divided into three parts, the book first devotes itself to the general theory of fuzzy control systems. The second part deals with a variety of methodologies and algorithms used in the analysis and design of fuzzy controllers. The various paradigms include fuzzy reasoning models, fuzzy neural networks, fuzzy expert systems, and genetic algorithms. The final part considers current applications of fuzzy control systems. This book should be required reading for researchers, practitioners, and students interested in fuzzy control systems, artificial intelligence, and fuzzy sets and systems.
Author | : S.G. Tzafestas |
Publisher | : Springer Science & Business Media |
Total Pages | : 573 |
Release | : 2012-12-06 |
Genre | : Technology & Engineering |
ISBN | : 9401154988 |
This book is concerned with Intelligent Control methods and applications. The field of intelligent control has been expanded very much during the recent years and a solid body of theoretical and practical results are now available. These results have been obtained through the synergetic fusion of concepts and techniques from a variety of fields such as automatic control, systems science, computer science, neurophysiology and operational research. Intelligent control systems have to perform anthropomorphic tasks fully autonomously or interactively with the human under known or unknown and uncertain environmental conditions. Therefore the basic components of any intelligent control system include cognition, perception, learning, sensing, planning, numeric and symbolic processing, fault detection/repair, reaction, and control action. These components must be linked in a systematic, synergetic and efficient way. Predecessors of intelligent control are adaptive control, self-organizing control, and learning control which are well documented in the literature. Typical application examples of intelligent controls are intelligent robotic systems, intelligent manufacturing systems, intelligent medical systems, and intelligent space teleoperators. Intelligent controllers must employ both quantitative and qualitative information and must be able to cope with severe temporal and spatial variations, in addition to the fundamental task of achieving the desired transient and steady-state performance. Of course the level of intelligence required in each particular application is a matter of discussion between the designers and users. The current literature on intelligent control is increasing, but the information is still available in a sparse and disorganized way.
Author | : Rudolf Kruse |
Publisher | : Springer-Verlag |
Total Pages | : 327 |
Release | : 2013-03-08 |
Genre | : Technology & Engineering |
ISBN | : 3322868257 |
This book contains a selection of revised papers and state-of-the-art overviews on current trends and future perspectives of fuzzy systems. A major aim is to address theoretical as well as application-oriented issues and to contribute to the foundation of concepts, methods, and tools in this field. The book is written by researchers who attended the workshop "Fuzzy Systems '93 - Management of Uncertain Information" (Braunschweig, Germany, October 21-22, 1993), organized by the German Society of Computer Science (GI), the German Computer Science Academy (DIA), and the University of Braunschweig.Dieses Buch enthält ausgewählte und auf neuesten Stand gebrachte Fachaufsätze und "State of the Art"-Übersichtsartikel in englischer Sprache. Sie geben einen Überblick über aktuelle Trends sowie Zukunftsperspektiven der Fuzzy-Systeme. Besonderer Wert wird darauf gelegt, daß das Buch in einem ausgewogenen Verhältnis von Theorie und Praxis zur Fundierung von Konzepten, Methoden und Werkzeugen beiträgt. Hervorgegangen ist das Werk aus einem von der Gesellschaft für Informatik (GI), der Deutschen Informatik Akademie (DIA) und der TU Braunschweig gemeinsam veranstalteten GI-Workshop "Fuzzy-Systeme '93 - Management unsicherer Informationen" (Braunschweig, 21.-22.10.1993). Die Aufsätze wurden überarbeitet und um Überblicksartikel ergänzt, geschrieben von H. J. Zimmermann, H. Hellendorn, D. Nauck, C. Freksa, S. Gottwald und K. D. Meyer-Gramann.