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System Identification And Adaptive Control

Author: Yiannis Boutalis
Publisher: Springer Science & Business
ISBN: 3319063642
Size: 16.24 MB
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Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.

Advances In Neural Networks Isnn 2007

Author: Derong Liu
Publisher: Springer
ISBN: 3540723838
Size: 68.42 MB
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This book is part of a three volume set that constitutes the refereed proceedings of the 4th International Symposium on Neural Networks, ISNN 2007, held in Nanjing, China in June 2007. Coverage includes neural networks for control applications, robotics, data mining and feature extraction, chaos and synchronization, support vector machines, fault diagnosis/detection, image/video processing, and applications of neural networks.

Computational Intelligence Theory And Applications

Author: Bernd Reusch
Publisher: Springer Science & Business Media
ISBN: 9783540628682
Size: 21.93 MB
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This book constitutes the refereed proceedings of the International Conference on Computational Intelligence held in Dortmund, Germany, as the 5th Fuzzy Days, in April 1997. Besides three invited contributions, the book presents 53 revised full papers selected from a total of 130 submissions. Also included are 35 posters documenting a broad scope of applications of computational intelligence techniques in a variety of areas. The volume addresses all current issues in computational intelligence, e.g. fuzzy logic, fuzzy control, neural networks, evolutionary algorithms, genetic programming, neuro-fuzzy systems, adaptation and learning, machine learning, etc.

Nonlinear System Identification

Author: Oliver Nelles
Publisher: Springer Science & Business Media
ISBN: 9783540673699
Size: 74.45 MB
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The goal of this book is to provide engineers and scientIsts in academia and industry with a thorough understanding of the underlying principles of nonlinear system identification. The reader will be able to apply the discussed models and methods to real problems with the necessary confidence and the awareness of potential difficulties that may arise in practice. This book is self-contained in the sense that it requires merely basic knowledge of matrix algebra, signals and systems, and statistics. Therefore, it also serves as an introduction to linear system identification and gives a practical overview on the major optimization methods used in engineering. The emphasis of this book is on an intuitive understanding of the subject and the practical application of the discussed techniques. It is not written in a theorem/proof style; rather the mathematics is kept to a minimum and the pursued ideas are illustrated by numerous figures, examples, and real-world applications. Fifteen years ago, nonlinear system identification was a field of several ad-hoc approaches, each applicable only to a very restricted class of systems. With the advent of neural networks, fuzzy models, and modern structure opti mization techniques a much wider class of systems can be handled. Although one major characteristic of nonlinear systems is that almost every nonlinear system is unique, tools have been developed that allow the use of the same ap proach for a broad variety of systems.

Foundations Of Neuro Fuzzy Systems

Author: Detlef Nauck
Publisher: Wiley
ISBN:
Size: 10.83 MB
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Neuro-Fuzzy Systems reflects the strong current trend in intelligent systems research towards the integration of neural networks and fuzzy technology. Systems exploiting these two techniques have the advantage of becoming both smarter and more applicable. This book explains the general principles of neuro-fuzzy development, as a means of enhancing the performance of a control or data analysis system.

Advances In Computational Intelligence

Author: Joan Cabestany
Publisher: Springer Science & Business Media
ISBN: 3642215009
Size: 58.70 MB
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This two-volume set LNCS 6691 and 6692 constitutes the refereed proceedings of the 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, held in Torremolinos-Málaga, Spain, in June 2011. The 154 revised papers were carefully reviewed and selected from 202 submissions for presentation in two volumes. The first volume includes 69 papers organized in topical sections on mathematical and theoretical methods in computational intelligence; learning and adaptation; bio-inspired systems and neuro-engineering; hybrid intelligent systems; applications of computational intelligence; new applications of brain-computer interfaces; optimization algorithms in graphic processing units; computing languages with bio-inspired devices and multi-agent systems; computational intelligence in multimedia processing; and biologically plausible spiking neural processing.

Knowledge Based Intelligent System Advancements Systemic And Cybernetic Approaches

Author: Jozefczyk, Jerzy
Publisher: IGI Global
ISBN: 1616928131
Size: 50.19 MB
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Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches presents selected new AI–based ideas and methods for analysis and decision making in intelligent information systems derived using systemic and cybernetic approaches. This book is useful for researchers, practitioners and students interested intelligent information retrieval and processing, machine learning and adaptation, knowledge discovery, applications of fuzzy based methods and neural networks.

Fuzzy Cognitive Maps

Author: Michael Glykas
Publisher: Springer
ISBN: 3642032206
Size: 74.98 MB
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This important edited volume is the first such book ever published on fuzzy cognitive maps (FCMs). Professor Michael Glykas has done an exceptional job in bringing together and editing its seventeen chapters. The volume appears nearly a quarter century after my original article “Fuzzy Cognitive Maps” appeared in the International Journal of Man-Machine Studies in 1986. The volume accordingly reflects many years of research effort in the development of FCM theory and applications—and portends many more decades of FCM research and applications to come. FCMs are fuzzy feedback models of causality. They combine aspects of fuzzy logic, neural networks, semantic networks, expert systems, and nonlinear dynamical systems. That rich structure endows FCMs with their own complexity and lets them apply to a wide range of problems in engineering and in the soft and hard sciences. Their partial edge connections allow a user to directly represent causality as a matter of degree and to learn new edge strengths from training data. Their directed graph structure allows forward or what-if inferencing. FCM cycles or feedback paths allow for complex nonlinear dynamics. Control of FCM nonlinear dynamics can in many cases let the user encode and decode concept patterns as fixed-point attractors or limit cycles or perhaps as more exotic dynamical equilibria. These global equilibrium patterns are often “hidden” in the nonlinear dynamics. The user will not likely see these global patterns by simply inspecting the local causal edges or nodes of large FCMs.

Fuzzy Control And Fuzzy Systems

Author: Witold Pedrycz
Publisher: Research Studies Pre
ISBN: 9780863801310
Size: 15.26 MB
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The second edition of this book provides extensively updated coverage of fuzzy control and fuzzy systems. Particular emphasis is placed on the role of fuzzy sets in control engineering, to provide flexible control algorithms. Significant new material is included. The author first provides information on fuzzy sets and the concept of fuzzy control. He reviews selected applications, and highlights their origin. Later chapters consider design aspects and theoretical developments in the design of fuzzy controllers. A special emphasis is focused on the processing of fuzzy information with the aid of fuzzy relational structures and their extensions, giving rise to fuzzy neural networks. The book addresses a novel approach towards designing fuzzy controllers, which takes advantage of the knowledge representation capabilities of fuzzy sets and of the learning abilities of neural networks. There is also comprehensive coverage of the paradigms and algorithms of fuzzy modelling.

Industrial Applications Of Fuzzy Control

Author: Michio Sugeno
Publisher: North Holland
ISBN:
Size: 45.18 MB
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This volume focuses on the practical applications of fuzzy control, which is one of the most promising research fields in fuzzy engineering. Control engineers in many fields can benefit from these case studies, which include the control of trains, aircraft, robots, and various industrial processes. Also featured is a comprehensive ``Annotated Bibliography of Fuzzy Control''.