Kalman-Bucy Filters PDF Download

Author: Karl Brammer
Publisher: Artech House Publishers
ISBN:
Category : Mathematics
Languages : en
Pages : 414

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Author: Peter A. Ruymgaart
Publisher: Springer Science & Business Media
ISBN: 3642733417
Category : Mathematics
Languages : en
Pages : 182

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Book Description
The second edition has not deviated significantly from the first. The printing of this edition, however, has allowed us to make a number of corrections which escaped our scrutiny at the time of the first printing, and to generally improve and tighten our presentation of the material. Many of these changes were suggested to us by colleagues and readers and their kindness in doing so is greatly appreciated. Delft, The Netherlands and P. A. Ruymgaart Buffalo, New York, December, 1987 T. T. Soong Preface to the First Edition Since their introduction in the mid 1950s, the filtering techniques developed by Kalman, and by Kalman and Bucy have been widely known and widely used in all areas of applied sciences. Starting with applications in aerospace engineering, their impact has been felt not only in all areas of engineering but as all also in the social sciences, biological sciences, medical sciences, as well other physical sciences. Despite all the good that has come out of this devel opment, however, there have been misuses because the theory has been used mainly as a tool or a procedure by many applied workers without fully understanding its underlying mathematical workings. This book addresses a mathematical approach to Kalman-Bucy filtering and is an outgrowth of lectures given at our institutions since 1971 in a sequence of courses devoted to Kalman-Bucy filters.

Author: P a Ruymgaart
Publisher:
ISBN: 9783642968433
Category :
Languages : en
Pages : 184

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Author: C. K. Chui
Publisher: Springer
ISBN:
Category : Computers
Languages : en
Pages : 218

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Book Description

Author: Mohinder S. Grewal
Publisher: John Wiley & Sons
ISBN: 111898496X
Category : Technology & Engineering
Languages : en
Pages : 639

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Book Description
The definitive textbook and professional reference on Kalman Filtering – fully updated, revised, and expanded This book contains the latest developments in the implementation and application of Kalman filtering. Authors Grewal and Andrews draw upon their decades of experience to offer an in-depth examination of the subtleties, common pitfalls, and limitations of estimation theory as it applies to real-world situations. They present many illustrative examples including adaptations for nonlinear filtering, global navigation satellite systems, the error modeling of gyros and accelerometers, inertial navigation systems, and freeway traffic control. Kalman Filtering: Theory and Practice Using MATLAB, Fourth Edition is an ideal textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self-instruction or review by practicing engineers and scientists who want to learn more about this important topic.

Author: Donald E. Catlin
Publisher: Springer Science & Business Media
ISBN: 1461245281
Category : Technology & Engineering
Languages : en
Pages : 286

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Book Description
In 1960, R. E. Kalman published his celebrated paper on recursive min imum variance estimation in dynamical systems [14]. This paper, which introduced an algorithm that has since been known as the discrete Kalman filter, produced a virtual revolution in the field of systems engineering. Today, Kalman filters are used in such diverse areas as navigation, guid ance, oil drilling, water and air quality, and geodetic surveys. In addition, Kalman's work led to a multitude of books and papers on minimum vari ance estimation in dynamical systems, including one by Kalman and Bucy on continuous time systems [15]. Most of this work was done outside of the mathematics and statistics communities and, in the spirit of true academic parochialism, was, with a few notable exceptions, ignored by them. This text is my effort toward closing that chasm. For mathematics students, the Kalman filtering theorem is a beautiful illustration of functional analysis in action; Hilbert spaces being used to solve an extremely important problem in applied mathematics. For statistics students, the Kalman filter is a vivid example of Bayesian statistics in action. The present text grew out of a series of graduate courses given by me in the past decade. Most of these courses were given at the University of Mas sachusetts at Amherst.

Author: Wing Hong Lee
Publisher:
ISBN:
Category : Continuous-time filters
Languages : en
Pages : 50

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Author: Michael Athans
Publisher:
ISBN:
Category : Kalman filtering
Languages : en
Pages : 35

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Book Description
The purpose of this report is to examine the properties of Kalman-Bucy filters, especially in the case of mismatching, i.e., when the nominal parameters used in the realization of the Kalman-Bucy filter are different from the actual plant parameters. In such cases, the mismatched filters give rise to bias and RMS errors. By making tests upon signals that appear in the filter, e.g., the residuals, one can detect the existence of mismatching. Hence, by knowing the properties of both matched and mismatched filters, one can then attempt to correct the estimates of the mismatched filters by on-line signal processing. (Author).

Author:
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: Frank L. Lewis
Publisher: CRC Press
ISBN: 1420008293
Category : Technology & Engineering
Languages : en
Pages : 546

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Book Description
More than a decade ago, world-renowned control systems authority Frank L. Lewis introduced what would become a standard textbook on estimation, under the title Optimal Estimation, used in top universities throughout the world. The time has come for a new edition of this classic text, and Lewis enlisted the aid of two accomplished experts to bring the book completely up to date with the estimation methods driving today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second Edition reflects new developments in estimation theory and design techniques. As the title suggests, the major feature of this edition is the inclusion of robust methods. Three new chapters cover the robust Kalman filter, H-infinity filtering, and H-infinity filtering of discrete-time systems. Modern Tools for Tomorrow's Engineers This text overflows with examples that highlight practical applications of the theory and concepts. Design algorithms appear conveniently in tables, allowing students quick reference, easy implementation into software, and intuitive comparisons for selecting the best algorithm for a given application. In addition, downloadable MATLAB® code allows students to gain hands-on experience with industry-standard software tools for a wide variety of applications. This cutting-edge and highly interactive text makes teaching, and learning, estimation methods easier and more modern than ever.