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e-Book Stability Analysis and Nonlinear Observer Design using Takagi-Sugeno Fuzzy Models (Studies in Fuzziness and Soft Computing) download

e-Book Stability Analysis and Nonlinear Observer Design using Takagi-Sugeno Fuzzy Models (Studies in Fuzziness and Soft Computing) download

by Zsófia Lendek,T. M. Guerra,Robert Babuška,Bart De Schutter

ISBN: 3642167756
ISBN13: 978-3642167751
Language: English
Publisher: Springer; 2011 edition (October 27, 2010)
Pages: 196
Category: Computer Science
Subategory: Technologies

ePub size: 1564 kb
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Studies in Fuzziness and Soft Computing

Studies in Fuzziness and Soft Computing. 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.

by Zsófia Lendek (Author), T. M. Guerra (Author), Robert Babuška (Author), Bart De Schutter (Author) & 1 more. ISBN-13: 978-3642167751. 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.

Takagi-Sugeno models are known to be universal approximators and, in addition, a broad class of. .

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. oceedings{A, title {Stability Analysis and Nonlinear Observer Design Using Takagi-Sugeno Fuzzy Models}, author {Zs{'o}fia Lendek and Thierry-Marie Guerra and Robert Babu{vs}ka and Bart De Schutter}, booktitle {Studies in Fuzziness and Soft Computing}, year {2010} }.

Takagi-Sugeno models are known to be universal approximators and, in.This book presents stability analysis and observer design methods for nonlinear systems, represented by TS fuzzy models.

Stability Analysis and Nonlinear Observer Design Using Takagi-Sugeno Fuzzy Models. For analysis and design of nonlinear systems, T-S technique is a very useful tool, because T-S fuzzy model has been proved to be a good representation for a certain class of nonlinear systems and be thought of as universal approximators for the nonlinear systems. Moreover, the nonlinear systems are represented by a set of local linear models interpolated by membership functions.

Focusing on the Takagi Sugeno (TS) fuzzy model, this volume provides a range of methods and tools to design .

Focusing on the Takagi Sugeno (TS) fuzzy model, this volume provides a range of methods and tools to design observers for nonlinear systems. Readers will find an in-depth theoretic analysis accompanied by illustrative examples and simulations of real-world systems.

Zsófia Lendek, Thierry Marie Guerra, Robert Babuška, and Bart De Schutter, Stability analysis and nonlinear observer design using Takagi-Sugeno fuzzy models, Studies in Fuzziness and Soft Computing, vol. 262, pp. 1–205, 2010. View at Publisher · View at Google Scholar.

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Stability analysis and nonlinear observer design using Takagi-Sugeno fuzzy models, volume 26. Design of observers for Takagi-Sugeno descriptor systems with unknown inputs and application to fault diagnosis. IET Control Theory and Applications, 1(5), 1487–1495

Stability analysis and nonlinear observer design using Takagi-Sugeno fuzzy models, volume 262. Springer. IET Control Theory and Applications, 1(5), 1487–1495. Ohtake, . Tanaka, . and Wang, .

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
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