System Identification Of Stochastic Nonlinear Dynamic Systems Using Takagi Sugeno Fuzzy Models

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System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models

Salman Zaidi
System Identification of Stochastic Nonlinear Dynamic Systems using Takagi Sugeno Fuzzy Models Book PDF

Author : Salman Zaidi
Publisher : kassel university press GmbH
Page : 155 pages
File Size : 42,8 Mb
Release : 2019-02-22
Category : Fuzzy systems
ISBN : 9783737606509

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System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models by Salman Zaidi Pdf

Some novel approaches to estimate Nonlinear Output Error (NOE) models using TS fuzzy models for a class of nonlinear dynamic systems having variability in their outputs is presented in this dissertation. Instead of using unrealistic assumptions about uncertainty, the most common of which is normality, the proposed methodology tends to capture effects caused by the real uncertainty observed in the data. The methodology requires that the identification method must be repeated offline a number of times under similar conditions. This leads to multiple inputoutput time series from the underlying system. These time series are preprocessed using the techniques of statistics and probability theory to generate the envelopes of response at each time instant. By incorporating interval data in fuzzy modelling and using the theory of symbolic interval-valued data, a TS fuzzy model with interval antecedent and consequent parameters is obtained. The proposed identification algorithm provides for a model for predicting the center-valued response as well as envelopes as the measure of uncertainty in system output.

Stochastic Control

Chris Myers
Stochastic Control Book PDF

Author : Chris Myers
Publisher : BoD – Books on Demand
Page : 663 pages
File Size : 54,8 Mb
Release : 2010-08-17
Category : Computers
ISBN : 9789533071213

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Stochastic Control by Chris Myers Pdf

Uncertainty presents significant challenges in the reasoning about and controlling of complex dynamical systems. To address this challenge, numerous researchers are developing improved methods for stochastic analysis. This book presents a diverse collection of some of the latest research in this important area. In particular, this book gives an overview of some of the theoretical methods and tools for stochastic analysis, and it presents the applications of these methods to problems in systems theory, science, and economics.

Stability Analysis and Nonlinear Observer Design using Takagi-Sugeno Fuzzy Models

Zsófia Lendek,T. M. Guerra,Robert Babuška,Bart De Schutter
Stability Analysis and Nonlinear Observer Design using Takagi Sugeno Fuzzy Models Book PDF

Author : Zsófia Lendek,T. M. Guerra,Robert Babuška,Bart De Schutter
Publisher : Springer
Page : 196 pages
File Size : 51,7 Mb
Release : 2010-11-26
Category : Technology & Engineering
ISBN : 9783642167768

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Stability Analysis and Nonlinear Observer Design using Takagi-Sugeno Fuzzy Models by Zsófia Lendek,T. M. Guerra,Robert Babuška,Bart De Schutter Pdf

Many problems in decision making, monitoring, fault detection, and control require the knowledge of state variables and time-varying parameters that are not directly measured by sensors. In such situations, observers, or estimators, can be employed that use the measured input and output signals along with a dynamic model of the system in order to estimate the unknown states or parameters. An essential requirement in designing an observer is to guarantee the convergence of the estimates to the true values or at least to a small neighborhood around the true values. However, for nonlinear, large-scale, or time-varying systems, the design and tuning of an observer is generally complicated and involves large computational costs. This book provides a range of methods and tools to design observers for nonlinear systems represented by a special type of a dynamic nonlinear model -- the Takagi--Sugeno (TS) fuzzy model. The TS model is a convex combination of affine linear models, which facilitates its stability analysis and observer design by using effective algorithms based on Lyapunov functions and linear matrix inequalities. Takagi--Sugeno models are known to be universal approximators and, in addition, a broad class of nonlinear systems can be exactly represented as a TS system. Three particular structures of large-scale TS models are considered: cascaded systems, distributed systems, and systems affected by unknown disturbances. The reader will find in-depth theoretic analysis accompanied by illustrative examples and simulations of real-world systems. Stability analysis of TS fuzzy systems is addressed in detail. The intended audience are graduate students and researchers both from academia and industry. For newcomers to the field, the book provides a concise introduction dynamic TS fuzzy models along with two methods to construct TS models for a given nonlinear system

Evolving Intelligent Systems

Plamen Angelov,Dimitar P. Filev,Nik Kasabov
Evolving Intelligent Systems Book PDF

Author : Plamen Angelov,Dimitar P. Filev,Nik Kasabov
Publisher : John Wiley & Sons
Page : 464 pages
File Size : 50,7 Mb
Release : 2010-03-25
Category : Computers
ISBN : 0470569956

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Evolving Intelligent Systems by Plamen Angelov,Dimitar P. Filev,Nik Kasabov Pdf

From theory to techniques, the first all-in-one resource for EIS There is a clear demand in advanced process industries, defense, and Internet and communication (VoIP) applications for intelligent yet adaptive/evolving systems. Evolving Intelligent Systems is the first self- contained volume that covers this newly established concept in its entirety, from a systematic methodology to case studies to industrial applications. Featuring chapters written by leading world experts, it addresses the progress, trends, and major achievements in this emerging research field, with a strong emphasis on the balance between novel theoretical results and solutions and practical real-life applications. Explains the following fundamental approaches for developing evolving intelligent systems (EIS): the Hierarchical Prioritized Structure the Participatory Learning Paradigm the Evolving Takagi-Sugeno fuzzy systems (eTS+) the evolving clustering algorithm that stems from the well-known Gustafson-Kessel offline clustering algorithm Emphasizes the importance and increased interest in online processing of data streams Outlines the general strategy of using the fuzzy dynamic clustering as a foundation for evolvable information granulation Presents a methodology for developing robust and interpretable evolving fuzzy rule-based systems Introduces an integrated approach to incremental (real-time) feature extraction and classification Proposes a study on the stability of evolving neuro-fuzzy recurrent networks Details methodologies for evolving clustering and classification Reveals different applications of EIS to address real problems in areas of: evolving inferential sensors in chemical and petrochemical industry learning and recognition in robotics Features downloadable software resources Evolving Intelligent Systems is the one-stop reference guide for both theoretical and practical issues for computer scientists, engineers, researchers, applied mathematicians, machine learning and data mining experts, graduate students, and professionals.

Advances in Neural Networks - ISNN 2007

Derong Liu,Shumin Fei,Zeng-Guang Hou,Huaguang Zhang,Changyin Sun
Advances in Neural Networks ISNN 2007 Book PDF

Author : Derong Liu,Shumin Fei,Zeng-Guang Hou,Huaguang Zhang,Changyin Sun
Publisher : Springer
Page : 1359 pages
File Size : 45,6 Mb
Release : 2007-07-14
Category : Computers
ISBN : 9783540723837

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Advances in Neural Networks - ISNN 2007 by Derong Liu,Shumin Fei,Zeng-Guang Hou,Huaguang Zhang,Changyin Sun Pdf

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.

Stochastic Distribution Control System Design

Lei Guo,Hong Wang
Stochastic Distribution Control System Design Book PDF

Author : Lei Guo,Hong Wang
Publisher : Springer Science & Business Media
Page : 201 pages
File Size : 48,9 Mb
Release : 2010-05-13
Category : Technology & Engineering
ISBN : 9781849960304

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Stochastic Distribution Control System Design by Lei Guo,Hong Wang Pdf

A recent development in SDC-related problems is the establishment of intelligent SDC models and the intensive use of LMI-based convex optimization methods. Within this theoretical framework, control parameter determination can be designed and stability and robustness of closed-loop systems can be analyzed. This book describes the new framework of SDC system design and provides a comprehensive description of the modelling of controller design tools and their real-time implementation. It starts with a review of current research on SDC and moves on to some basic techniques for modelling and controller design of SDC systems. This is followed by a description of controller design for fixed-control-structure SDC systems, PDF control for general input- and output-represented systems, filtering designs, and fault detection and diagnosis (FDD) for SDC systems. Many new LMI techniques being developed for SDC systems are shown to have independent theoretical significance for robust control and FDD problems.

System Identification 2003

Paul Van Den Hof,Bo Wahlberg,Siep Weiland
System Identification 2003 Book PDF

Author : Paul Van Den Hof,Bo Wahlberg,Siep Weiland
Publisher : Elsevier
Page : 2088 pages
File Size : 42,8 Mb
Release : 2004-06-29
Category : Technology & Engineering
ISBN : 9780080913155

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System Identification 2003 by Paul Van Den Hof,Bo Wahlberg,Siep Weiland Pdf

The scope of the symposium covers all major aspects of system identification, experimental modelling, signal processing and adaptive control, ranging from theoretical, methodological and scientific developments to a large variety of (engineering) application areas. It is the intention of the organizers to promote SYSID 2003 as a meeting place where scientists and engineers from several research communities can meet to discuss issues related to these areas. Relevant topics for the symposium program include: Identification of linear and multivariable systems, identification of nonlinear systems, including neural networks, identification of hybrid and distributed systems, Identification for control, experimental modelling in process control, vibration and modal analysis, model validation, monitoring and fault detection, signal processing and communication, parameter estimation and inverse modelling, statistical analysis and uncertainty bounding, adaptive control and data-based controller tuning, learning, data mining and Bayesian approaches, sequential Monte Carlo methods, including particle filtering, applications in process control systems, motion control systems, robotics, aerospace systems, bioengineering and medical systems, physical measurement systems, automotive systems, econometrics, transportation and communication systems *Provides the latest research on System Identification *Contains contributions written by experts in the field *Part of the IFAC Proceedings Series which provides a comprehensive overview of the major topics in control engineering.

Nonlinear System Identification

Oliver Nelles
Nonlinear System Identification Book PDF

Author : Oliver Nelles
Publisher : Springer Nature
Page : 1235 pages
File Size : 53,6 Mb
Release : 2020-09-09
Category : Science
ISBN : 9783030474393

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Nonlinear System Identification by Oliver Nelles Pdf

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.

Nonlinear System Identification

Oliver Nelles
Nonlinear System Identification Book PDF

Author : Oliver Nelles
Publisher : Springer Science & Business Media
Page : 786 pages
File Size : 41,8 Mb
Release : 2013-03-09
Category : Technology & Engineering
ISBN : 9783662043233

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Nonlinear System Identification by Oliver Nelles Pdf

Written from an engineering point of view, this book covers the most common and important approaches for the identification of nonlinear static and dynamic systems. The book also provides the reader with the necessary background on optimization techniques, making it fully self-contained. The new edition includes exercises.

Fuzzy Control, Estimation and Diagnosis

Magdi S. Mahmoud
Fuzzy Control Estimation and Diagnosis Book PDF

Author : Magdi S. Mahmoud
Publisher : Springer
Page : 689 pages
File Size : 54,5 Mb
Release : 2017-06-15
Category : Technology & Engineering
ISBN : 9783319549545

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Fuzzy Control, Estimation and Diagnosis by Magdi S. Mahmoud Pdf

This textbook explains the principles of fuzzy systems in some depth together with information useful in realizing them within computational processes. The various algorithms and example problem solutions are a well-balanced and pertinent aid for research projects, laboratory work and graduate study. In addition to its worked examples, the book also uses end-of-chapter exercises as an instructional aid with a downloadable solutions manual available to instructors. The content of the book is developed and extended from material taught for four years in the author’s classes. The text provides a broad overview of fuzzy control, estimation and fault diagnosis. It ranges over various classes of target system and modes of control and then turns to filtering, stabilization, and fault detection and diagnosis. Applications, simulation tools and an appendix on algebraic inequalities complete a unified approach to the analysis of single and interconnected fuzzy systems. Fuzzy Control, Estimation and Fault Detection is a guide for final-year undergraduate and graduate students of electrical and mechanical engineering, computer science and information technology, and will also be instructive for professionals in the information technology sector.

Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019)

Rui Wang,Zengqiang Chen,Weicun Zhang,Quanmin Zhu
Proceedings of the 11th International Conference on Modelling Identification and Control ICMIC2019 Book PDF

Author : Rui Wang,Zengqiang Chen,Weicun Zhang,Quanmin Zhu
Publisher : Springer Nature
Page : 1340 pages
File Size : 47,7 Mb
Release : 2019-12-03
Category : Technology & Engineering
ISBN : 9789811504747

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Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019) by Rui Wang,Zengqiang Chen,Weicun Zhang,Quanmin Zhu Pdf

This book includes original, peer-reviewed research papers from the 11th International Conference on Modelling, Identification and Control (ICMIC2019), held in Tianjin, China on July 13-15, 2019. The topics covered include but are not limited to: System Identification, Linear/Nonlinear Control Systems, Data-driven Modelling and Control, Process Modelling and Process Control, Fault Diagnosis and Reliable Control, Intelligent Systems, and Machine Learning and Artificial Intelligence.The papers showcased here share the latest findings on methodologies, algorithms and applications in modelling, identification, and control, integrated with Artificial Intelligence (AI), making the book a valuable asset for researchers, engineers, and university students alike.

Fault Diagnosis and Sustainable Control of Wind Turbines

Silvio Simani,Saverio Farsoni
Fault Diagnosis and Sustainable Control of Wind Turbines Book PDF

Author : Silvio Simani,Saverio Farsoni
Publisher : Butterworth-Heinemann
Page : 228 pages
File Size : 48,9 Mb
Release : 2018-01-02
Category : Technology & Engineering
ISBN : 9780128129852

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Fault Diagnosis and Sustainable Control of Wind Turbines by Silvio Simani,Saverio Farsoni Pdf

Fault Diagnosis and Sustainable Control of Wind Turbines: Robust Data-Driven and Model-Based Strategies discusses the development of reliable and robust fault diagnosis and fault-tolerant (‘sustainable’) control schemes by means of data-driven and model-based approaches. These strategies are able to cope with unknown nonlinear systems and noisy measurements. The book also discusses simpler solutions relying on data-driven and model-based methodologies, which are key when on-line implementations are considered for the proposed schemes. The book targets both professional engineers working in industry and researchers in academic and scientific institutions. In order to improve the safety, reliability and efficiency of wind turbine systems, thus avoiding expensive unplanned maintenance, the accommodation of faults in their early occurrence is fundamental. To highlight the potential of the proposed methods in real applications, hardware–in–the–loop test facilities (representing realistic wind turbine systems) are considered to analyze the digital implementation of the designed solutions. The achieved results show that the developed schemes are able to maintain the desired performances, thus validating their reliability and viability in real-time implementations. Different groups of readers—ranging from industrial engineers wishing to gain insight into the applications' potential of new fault diagnosis and sustainable control methods, to the academic control community looking for new problems to tackle—will find much to learn from this work. Provides wind turbine models with varying complexity, as well as the solutions proposed and developed by the authors Addresses in detail the design, development and realistic implementation of fault diagnosis and fault tolerant control strategies for wind turbine systems Addresses the development of sustainable control solutions that, in general, do not require the introduction of further or redundant measurements Proposes active fault tolerant ('sustainable') solutions that are able to maintain the wind turbine working conditions with gracefully degraded performance before required maintenance can occur Presents full coverage of the diagnosis and fault tolerant control problem, starting from the modeling and identification and finishing with diagnosis and fault tolerant control approaches Provides MATLAB and Simulink codes for the solutions proposed

Artificial Intelligence in Energy and Renewable Energy Systems

Soteris Kalogirou
Artificial Intelligence in Energy and Renewable Energy Systems Book PDF

Author : Soteris Kalogirou
Publisher : Nova Publishers
Page : 488 pages
File Size : 51,7 Mb
Release : 2007
Category : Computers
ISBN : 1600212611

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Artificial Intelligence in Energy and Renewable Energy Systems by Soteris Kalogirou Pdf

This book presents state of the art applications of artificial intelligence in energy and renewable energy systems design and modelling. It covers such topics as solar energy, wind energy, biomass and hydrogen as well as building services systems, power generation systems, combustion processes and refrigeration. In all these areas applications of artificial intelligence methods such as artificial neural networks, genetic algorithms, fuzzy logic and a combination of the above, called hybrid systems, are included. The book is intended for a wide audience ranging from the undergraduate level up to the research academic and industrial communities dealing with modelling and performance prediction of energy and renewable energy systems.

Forging New Frontiers: Fuzzy Pioneers II

Masoud Nikravesh,Lofti A. Zadeh
Forging New Frontiers Fuzzy Pioneers II Book PDF

Author : Masoud Nikravesh,Lofti A. Zadeh
Publisher : Springer
Page : 433 pages
File Size : 48,5 Mb
Release : 2007-10-30
Category : Technology & Engineering
ISBN : 9783540731856

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Forging New Frontiers: Fuzzy Pioneers II by Masoud Nikravesh,Lofti A. Zadeh Pdf

The chapters of the book are evolved from presentations made by selected participants at the 2005 BISC International Special Event, held at the University of California at Berkely. The papers include reports from the different front of soft computing in various industries and address the problems of different fields of research in fuzzy logic, fuzzy set and soft computing. The book provides a collection of forty-four articles in two volumes.

Nonlinear system identification. 2. Nonlinear system structure identification

Robert Haber,László Keviczky
Nonlinear system identification 2 Nonlinear system structure identification Book PDF

Author : Robert Haber,László Keviczky
Publisher : Springer Science & Business Media
Page : 428 pages
File Size : 54,5 Mb
Release : 1999
Category : Computers
ISBN : 0792358570

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Nonlinear system identification. 2. Nonlinear system structure identification by Robert Haber,László Keviczky Pdf

This is the second part of a two-volume handbook presenting a comprehensive overview of nonlinear dynamic system identification. The books include many aspects of nonlinear processes such as modelling, parameter estimation, structure search, nonlinearity and model validity tests.