Multiple Model Approaches To Nonlinear Modelling And Control

Multiple Model Approaches To Nonlinear Modelling And Control

Author: R Murray-Smith

Publisher: CRC Press

ISBN: 9781000124071

Category: Technology & Engineering

Page: 360

View: 976

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This work presents approaches to modelling and control problems arising from conditions of ever increasing nonlinearity and complexity. It prescribes an approach that covers a wide range of methods being combined to provide multiple model solutions. Many component methods are described, as well as discussion of the strategies available for building a successful multiple model approach.

Informatics in Control, Automation and Robotics

Informatics in Control, Automation and Robotics

Author: Oleg Gusikhin

Publisher: Springer Nature

ISBN: 9783030924423

Category: Technology & Engineering

Page: 632

View: 310

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The book focuses the latest endeavours relating researches and developments conducted in fields of Control, Robotics and Automation. Through more than ten revised and extended articles, the present book aims to provide the most up-to-date state-of-art of the aforementioned fields allowing researcher, PhD students and engineers not only updating their knowledge but also benefiting from the source of inspiration that represents the set of selected articles of the book. The deliberate intention of editors to cover as well theoretical facets of those fields as their practical accomplishments and implementations offers the benefit of gathering in a same volume a factual and well-balanced prospect of nowadays research in those topics. A special attention toward “Intelligent Robots and Control” may characterize another benefit of this book.

Design of Interpretable Fuzzy Systems

Design of Interpretable Fuzzy Systems

Author: Krzysztof Cpałka

Publisher: Springer

ISBN: 9783319528816

Category: Technology & Engineering

Page: 196

View: 450

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This book shows that the term “interpretability” goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.

Nonlinear System Identification

Nonlinear System Identification

Author: Oliver Nelles

Publisher: Springer Nature

ISBN: 9783030474393

Category: Science

Page: 1203

View: 360

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This book provides engineers and scientists in academia and industry with a thorough understanding of the underlying principles of nonlinear system identification. It equips them to apply the models and methods discussed to real problems with confidence, while also making them aware of potential difficulties that may arise in practice. Moreover, the book is self-contained, requiring only a basic grasp of matrix algebra, signals and systems, and statistics. Accordingly, it can also serve as an introduction to linear system identification, and provides a practical overview of the major optimization methods used in engineering. The focus is on gaining an intuitive understanding of the subject and the practical application of the techniques discussed. The book is not written in a theorem/proof style; instead, the mathematics is kept to a minimum, and the ideas covered are illustrated with numerous figures, examples, and real-world applications. In the past, nonlinear system identification was a field characterized by a variety of ad-hoc approaches, each applicable only to a very limited class of systems. With the advent of neural networks, fuzzy models, Gaussian process models, and modern structure optimization techniques, a much broader class of systems can now be handled. Although one major aspect of nonlinear systems is that virtually every one is unique, tools have since been developed that allow each approach to be applied to a wide variety of systems.

Fuzzy Systems: Concepts, Methodologies, Tools, and Applications

Fuzzy Systems: Concepts, Methodologies, Tools, and Applications

Author: Management Association, Information Resources

Publisher: IGI Global

ISBN: 9781522519096

Category: Mathematics

Page: 1765

View: 465

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There are a myriad of mathematical problems that cannot be solved using traditional methods. The development of fuzzy expert systems has provided new opportunities for problem-solving amidst uncertainties. Fuzzy Systems: Concepts, Methodologies, Tools, and Applications is a comprehensive reference source on the latest scholarly research and developments in fuzzy rule-based methods and examines both theoretical foundations and real-world utilization of these logic sets. Featuring a range of extensive coverage across innovative topics, such as fuzzy logic, rule-based systems, and fuzzy analysis, this is an essential publication for scientists, doctors, engineers, physicians, and researchers interested in emerging perspectives and uses of fuzzy systems in various sectors.

Soft Computing and Industry

Soft Computing and Industry

Author: Rajkumar Roy

Publisher: Springer Science & Business Media

ISBN: 9781447101239

Category: Technology & Engineering

Page: 852

View: 174

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Soft computing embraces various methodologies for the development of intelligent systems that have been successfully applied to a large number of real-world problems. Soft Computing in Industry contains a collection of papers that were presented at the 6th On-line World Conference on Soft Computing in Industrial Applications that was held in September 2001. It provides a comprehensive overview of recent theoretical developments in soft computing as well as of successful industrial applications. It is divided into seven parts covering material on: keynote papers on various subjects ranging from computing with autopoietic systems to the effects of the Internet on education; intelligent control; classification, clustering and optimization; image and signal processing; agents, multimedia and Internet; theoretical advances; prediction, design and diagnosis. The book is aimed at researchers and professional engineers who develop and apply intelligent systems in computer engineering.

Energy Efficient Non-Road Hybrid Electric Vehicles

Energy Efficient Non-Road Hybrid Electric Vehicles

Author: Johannes Unger

Publisher: Springer

ISBN: 9783319297965

Category: Technology & Engineering

Page: 116

View: 207

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This book analyzes the main problems in the real-time control of parallel hybrid electric powertrains in non-road applications that work in continuous high dynamic operation. It also provides practical insights into maximizing the energy efficiency and drivability of such powertrains. It introduces an energy-management control structure, which considers all the physical powertrain constraints and uses novel methodologies to predict the future load requirements to optimize the controller output in terms of the entire work cycle of a non-road vehicle. The load prediction includes a methodology for short-term loads as well as cycle detection methodology for an entire load cycle. In this way, the energy efficiency can be maximized, and fuel consumption and exhaust emissions simultaneously reduced. Readers gain deep insights into the topics that need to be considered in designing an energy and battery management system for non-road vehicles. It also becomes clear that only a combination of management systems can significantly increase the performance of a controller.

Field Programmable Logic and Applications

Field Programmable Logic and Applications

Author: Peter Y.K. Cheung

Publisher: Springer

ISBN: 9783540452348

Category: Computers

Page: 1182

View: 366

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This book contains the papers presented at the 13th International Workshop on Field Programmable Logic and Applications (FPL) held on September 1–3, 2003. The conference was hosted by the Institute for Systems and Computer Engineering-Research and Development of Lisbon (INESC-ID) and the Depa- ment of Electrical and Computer Engineering of the IST-Technical University of Lisbon, Portugal. The FPL series of conferences was founded in 1991 at Oxford University (UK), and has been held annually since: in Oxford (3 times), Vienna, Prague, Darmstadt,London,Tallinn,Glasgow,Villach,BelfastandMontpellier.Itbrings together academic researchers, industrial experts, users and newcomers in an - formal,welcomingatmospherethatencouragesproductiveexchangeofideasand knowledge between delegates. Exciting advances in ?eld programmable logic show no sign of slowing down. New grounds have been broken in architectures, design techniques, run-time - con?guration, and applications of ?eld programmable devices in several di?erent areas. Many of these innovations are reported in this volume. The size of FPL conferences has grown signi?cantly over the years. FPL in 2002 saw 214 papers submitted, representing an increase of 83% when compared to the year before. The interest and support for FPL in the programmable logic community continued this year with 216 papers submitted. The technical p- gram was assembled from 90 selected regular papers and 56 posters, resulting in this volume of proceedings. The program also included three invited plenary keynote presentations from LSI Logic, Xilinx and Cadence, and three industrial tutorials from Altera, Mentor Graphics and Dafca.

Fault Detection, Supervision and Safety of Technical Processes 2006

Fault Detection, Supervision and Safety of Technical Processes 2006

Author: Hong-Yue Zhang

Publisher: Elsevier

ISBN: 008055539X

Category: Science

Page: 1576

View: 171

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The safe and reliable operation of technical systems is of great significance for the protection of human life and health, the environment, and of the vested economic value. The correct functioning of those systems has a profound impact also on production cost and product quality. The early detection of faults is critical in avoiding performance degradation and damage to the machinery or human life. Accurate diagnosis then helps to make the right decisions on emergency actions and repairs. Fault detection and diagnosis (FDD) has developed into a major area of research, at the intersection of systems and control engineering, artificial intelligence, applied mathematics and statistics, and such application fields as chemical, electrical, mechanical and aerospace engineering. IFAC has recognized the significance of FDD by launching a triennial symposium series dedicated to the subject. The SAFEPROCESS Symposium is organized every three years since the first symposium held in Baden-Baden in 1991. SAFEPROCESS 2006, the 6th IFAC Symposium on Fault Detection, Supervision and Safety of Technical Processes was held in Beijing, PR China. The program included three plenary papers, two semi-plenary papers, two industrial talks by internationally recognized experts and 258 regular papers, which have been selected out of a total of 387 regular and invited papers submitted. * Discusses the developments and future challenges in all aspects of fault diagnosis and fault tolerant control * 8 invited and 36 contributed sessions included with a special session on the demonstration of process monitoring and diagnostic software tools

Adaptive Modelling, Estimation and Fusion from Data

Adaptive Modelling, Estimation and Fusion from Data

Author: Chris Harris

Publisher: Springer Science & Business Media

ISBN: 9783642182426

Category: Computers

Page: 323

View: 650

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This book brings together for the first time the complete theory of data based neurofuzzy modelling and the linguistic attributes of fuzzy logic in a single cohesive mathematical framework. After introducing the basic theory of data based modelling new concepts including extended additive and multiplicative submodels are developed. All of these algorithms are illustrated with benchmark examples to demonstrate their efficiency. The book aims at researchers and advanced professionals in time series modelling, empirical data modelling, knowledge discovery, data mining and data fusion.

Cluster Analysis for Data Mining and System Identification

Cluster Analysis for Data Mining and System Identification

Author: János Abonyi

Publisher: Springer Science & Business Media

ISBN: 9783764379889

Category: Mathematics

Page: 306

View: 849

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The aim of this book is to illustrate that advanced fuzzy clustering algorithms can be used not only for partitioning of the data. It can also be used for visualization, regression, classification and time-series analysis, hence fuzzy cluster analysis is a good approach to solve complex data mining and system identification problems. This book is oriented to undergraduate and postgraduate and is well suited for teaching purposes.

Predictive Modular Neural Networks

Predictive Modular Neural Networks

Author: Vassilios Petridis

Publisher: Springer Science & Business Media

ISBN: 9781461555551

Category: Science

Page: 314

View: 416

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The subject of this book is predictive modular neural networks and their ap plication to time series problems: classification, prediction and identification. The intended audience is researchers and graduate students in the fields of neural networks, computer science, statistical pattern recognition, statistics, control theory and econometrics. Biologists, neurophysiologists and medical engineers may also find this book interesting. In the last decade the neural networks community has shown intense interest in both modular methods and time series problems. Similar interest has been expressed for many years in other fields as well, most notably in statistics, control theory, econometrics etc. There is a considerable overlap (not always recognized) of ideas and methods between these fields. Modular neural networks come by many other names, for instance multiple models, local models and mixtures of experts. The basic idea is to independently develop several "subnetworks" (modules), which may perform the same or re lated tasks, and then use an "appropriate" method for combining the outputs of the subnetworks. Some of the expected advantages of this approach (when compared with the use of "lumped" or "monolithic" networks) are: superior performance, reduced development time and greater flexibility. For instance, if a module is removed from the network and replaced by a new module (which may perform the same task more efficiently), it should not be necessary to retrain the aggregate network.