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Nonlinear filteringmethods and appli...

Chandra, Kumar Pakki Bharani.

Nonlinear filteringmethods and applications /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Nonlinear filteringby Kumar Pakki Bharani Chandra, Da-Wei Gu.
其他題名:	methods and applications /
作者:	Chandra, Kumar Pakki Bharani.
其他作者:	Gu, Da-Wei.
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xix, 184 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Stochastic processes.
電子資源:	https://doi.org/10.1007/978-3-030-01797-2
ISBN:	9783030017972$q(electronic bk.)

Nonlinear filteringmethods and applications /
Chandra, Kumar Pakki Bharani.

Nonlinear filteringmethods and applications /[electronic resource] :by Kumar Pakki Bharani Chandra, Da-Wei Gu. - Cham :Springer International Publishing :2019. - xix, 184 p. :ill., digital ;24 cm.

Linear and Nonlinear Control Systems -- State Estimation and Prediction -- Linear Estimation Techniques -- Jacobian-Based Filters -- Unscented Kalman Filters -- Cubature Kalman Filters -- Variants of Cubature Kalman Filters -- Robustness Consideration of Filtering Algorithms.

This book gives readers in-depth know-how on methods of state estimation for nonlinear control systems. It starts with an introduction to dynamic control systems and system states and a brief description of the Kalman filter. In the following chapters, various state estimation techniques for nonlinear systems are discussed, including the extended, unscented and cubature Kalman filters, etc. The cubature Kalman filter and its variants are introduced in particular detail because of their efficiency and their ability to deal with systems with Gaussian and/or non-Gaussian noise. The book also discusses information-filter and square-root-filtering algorithms, useful for state estimation in some real-time control system design problems. A number of case studies are included in the book to illustrate the application of various nonlinear filtering algorithms. Nonlinear Filtering is written for academic and industrial researchers, engineers and research students who are interested in nonlinear control systems analysis and design. The chief features of the book include: dedicated coverage of recently developed nonlinear, Jacobian-free, filtering algorithms; examples illustrating the use of nonlinear filtering algorithms in real-world applications; detailed derivation and complete algorithms for nonlinear filtering methods help readers to a fundamental understanding and easier coding of those algorithms; and MATLAB® codes associated with case-study applications can be downloaded from the Springer Extra Materials website.

ISBN: 9783030017972$q(electronic bk.)

Standard No.: 10.1007/978-3-030-01797-2doiSubjects--Topical Terms:

181874
Stochastic processes.

LC Class. No.: QA274 / .C436 2019

Dewey Class. No.: 519.23

Nonlinear filteringmethods and applications /
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520 $a This book gives readers in-depth know-how on methods of state estimation for nonlinear control systems. It starts with an introduction to dynamic control systems and system states and a brief description of the Kalman filter. In the following chapters, various state estimation techniques for nonlinear systems are discussed, including the extended, unscented and cubature Kalman filters, etc. The cubature Kalman filter and its variants are introduced in particular detail because of their efficiency and their ability to deal with systems with Gaussian and/or non-Gaussian noise. The book also discusses information-filter and square-root-filtering algorithms, useful for state estimation in some real-time control system design problems. A number of case studies are included in the book to illustrate the application of various nonlinear filtering algorithms. Nonlinear Filtering is written for academic and industrial researchers, engineers and research students who are interested in nonlinear control systems analysis and design. The chief features of the book include: dedicated coverage of recently developed nonlinear, Jacobian-free, filtering algorithms; examples illustrating the use of nonlinear filtering algorithms in real-world applications; detailed derivation and complete algorithms for nonlinear filtering methods help readers to a fundamental understanding and easier coding of those algorithms; and MATLAB® codes associated with case-study applications can be downloaded from the Springer Extra Materials website.
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