Nonlinear Estimation
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Nonlinear Estimation
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Author : Gavin J.S. Ross
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Nonlinear Estimation written by Gavin J.S. Ross and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
Non-Linear Estimation is a handbook for the practical statistician or modeller interested in fitting and interpreting non-linear models with the aid of a computer. A major theme of the book is the use of 'stable parameter systems'; these provide rapid convergence of optimization algorithms, more reliable dispersion matrices and confidence regions for parameters, and easier comparison of rival models. The book provides insights into why some models are difficult to fit, how to combine fits over different data sets, how to improve data collection to reduce prediction variance, and how to program particular models to handle a full range of data sets. The book combines an algebraic, a geometric and a computational approach, and is illustrated with practical examples. A final chapter shows how this approach is implemented in the author's Maximum Likelihood Program, MLP.
Recursive Nonlinear Estimation
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Author : Rudolf Kulhavý
language : en
Publisher: Springer
Release Date : 1996-06-25
Recursive Nonlinear Estimation written by Rudolf Kulhavý and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-06-25 with Mathematics categories.
In a close analogy to matching data in Euclidean space, this monograph views parameter estimation as matching of the empirical distribution of data with a model-based distribution. Using an appealing Pythagorean-like geometry of the empirical and model distributions, the book brings a new solution to the problem of recursive estimation of non-Gaussian and nonlinear models which can be regarded as a specific approximation of Bayesian estimation. The cases of independent observations and controlled dynamic systems are considered in parallel; the former case giving initial insight into the latter case which is of primary interest to the control community. A number of examples illustrate the key concepts and tools used. This unique monograph follows some previous results on the Pythagorean theory of estimation in the literature (e.g., Chentsov, Csiszar and Amari) but extends the results to the case of controlled dynamic systems.
Estimation With Applications To Tracking And Navigation
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Author : Yaakov Bar-Shalom
language : en
Publisher: John Wiley & Sons
Release Date : 2004-03-22
Estimation With Applications To Tracking And Navigation written by Yaakov Bar-Shalom and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-03-22 with Technology & Engineering categories.
Expert coverage of the design and implementation of state estimation algorithms for tracking and navigation Estimation with Applications to Tracking and Navigation treats the estimation of various quantities from inherently inaccurate remote observations. It explains state estimator design using a balanced combination of linear systems, probability, and statistics. The authors provide a review of the necessary background mathematical techniques and offer an overview of the basic concepts in estimation. They then provide detailed treatments of all the major issues in estimation with a focus on applying these techniques to real systems. Other features include: * Problems that apply theoretical material to real-world applications * In-depth coverage of the Interacting Multiple Model (IMM) estimator * Companion DynaEst(TM) software for MATLAB(TM) implementation of Kalman filters and IMM estimators * Design guidelines for tracking filters Suitable for graduate engineering students and engineers working in remote sensors and tracking, Estimation with Applications to Tracking and Navigation provides expert coverage of this important area.
Max Plus Methods For Nonlinear Control And Estimation
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Author : William M. McEneaney
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-07-25
Max Plus Methods For Nonlinear Control And Estimation written by William M. McEneaney and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-07-25 with Mathematics categories.
The central focus of this book is the control of continuous-time/continuous-space nonlinear systems. Using new techniques that employ the max-plus algebra, the author addresses several classes of nonlinear control problems, including nonlinear optimal control problems and nonlinear robust/H-infinity control and estimation problems. Several numerical techniques are employed, including a max-plus eigenvector approach and an approach that avoids the curse-of-dimensionality. The max-plus-based methods examined in this work belong to an entirely new class of numerical methods for the solution of nonlinear control problems and their associated Hamilton–Jacobi–Bellman (HJB) PDEs; these methods are not equivalent to either of the more commonly used finite element or characteristic approaches. Max-Plus Methods for Nonlinear Control and Estimation will be of interest to applied mathematicians, engineers, and graduate students interested in the control of nonlinear systems through the implementation of recently developed numerical methods.
Optimal State Estimation
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Author : Dan Simon
language : en
Publisher: John Wiley & Sons
Release Date : 2006-06-19
Optimal State Estimation written by Dan Simon and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-06-19 with Technology & Engineering categories.
A bottom-up approach that enables readers to master and apply the latest techniques in state estimation This book offers the best mathematical approaches to estimating the state of a general system. The author presents state estimation theory clearly and rigorously, providing the right amount of advanced material, recent research results, and references to enable the reader to apply state estimation techniques confidently across a variety of fields in science and engineering. While there are other textbooks that treat state estimation, this one offers special features and a unique perspective and pedagogical approach that speed learning: * Straightforward, bottom-up approach begins with basic concepts and then builds step by step to more advanced topics for a clear understanding of state estimation * Simple examples and problems that require only paper and pen to solve lead to an intuitive understanding of how theory works in practice * MATLAB(r)-based source code that corresponds to examples in the book, available on the author's Web site, enables readers to recreate results and experiment with other simulation setups and parameters Armed with a solid foundation in the basics, readers are presented with a careful treatment of advanced topics, including unscented filtering, high order nonlinear filtering, particle filtering, constrained state estimation, reduced order filtering, robust Kalman filtering, and mixed Kalman/H? filtering. Problems at the end of each chapter include both written exercises and computer exercises. Written exercises focus on improving the reader's understanding of theory and key concepts, whereas computer exercises help readers apply theory to problems similar to ones they are likely to encounter in industry. With its expert blend of theory and practice, coupled with its presentation of recent research results, Optimal State Estimation is strongly recommended for undergraduate and graduate-level courses in optimal control and state estimation theory. It also serves as a reference for engineers and science professionals across a wide array of industries.
Nonlinear Filters
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Author : Hisashi Tanizaki
language : en
Publisher: Springer Science & Business Media
Release Date : 1996-08-16
Nonlinear Filters written by Hisashi Tanizaki and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-08-16 with Business & Economics categories.
Nonlinear and nonnormal filters are introduced and developed. Traditional nonlinear filters such as the extended Kalman filter and the Gaussian sum filter give biased filtering estimates, and therefore several nonlinear and nonnormal filters have been derived from the underlying probability density functions. The density-based nonlinear filters introduced in this book utilize numerical integration, Monte-Carlo integration with importance sampling or rejection sampling and the obtained filtering estimates are asymptotically unbiased and efficient. By Monte-Carlo simulation studies, all the nonlinear filters are compared. Finally, as an empirical application, consumption functions based on the rational expectation model are estimated for the nonlinear filters, where US, UK and Japan economies are compared.
Nonlinear Model Based Process Control
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Author : Rıdvan Berber
language : en
Publisher: Springer Science & Business Media
Release Date : 1998
Nonlinear Model Based Process Control written by Rıdvan Berber and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computers categories.
The increasingly competitive environment within which modern industry has to work means that processes have to be operated over a wider range of conditions in order to meet constantly changing performance targets. Add to this the fact that many industrial operations are nonlinear, and the need for on-line control algorithms for nonlinear processes becomes clear. Major progress has been booked in constrained model-based control and important issues of nonlinear process control have been solved. This text surveys the state-of-the-art in nonlinear model-based control technology, by writers who have actually created the scientific profile. A broad range of issues are covered in depth, from traditional nonlinear approaches to nonlinear model predictive control, from nonlinear process identification and state estimation to control-integrated design. Advances in the control of inverse response and unstable processes are presented. Comparisons with linear control are given, and case studies are used for illustration.
Neural Network Based State Estimation Of Nonlinear Systems
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Author : Heidar A. Talebi
language : en
Publisher: Springer
Release Date : 2009-12-04
Neural Network Based State Estimation Of Nonlinear Systems written by Heidar A. Talebi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-12-04 with Technology & Engineering categories.
"Neural Network-Based State Estimation of Nonlinear Systems" presents efficient, easy to implement neural network schemes for state estimation, system identification, and fault detection and Isolation with mathematical proof of stability, experimental evaluation, and Robustness against unmolded dynamics, external disturbances, and measurement noises.
Applied Optimal Estimation
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Author : The Analytic Sciences Corporation
language : en
Publisher: MIT Press
Release Date : 1974-05-15
Applied Optimal Estimation written by The Analytic Sciences Corporation and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1974-05-15 with Computers categories.
This is the first book on the optimal estimation that places its major emphasis on practical applications, treating the subject more from an engineering than a mathematical orientation. Even so, theoretical and mathematical concepts are introduced and developed sufficiently to make the book a self-contained source of instruction for readers without prior knowledge of the basic principles of the field. The work is the product of the technical staff of The Analytic Sciences Corporation (TASC), an organization whose success has resulted largely from its applications of optimal estimation techniques to a wide variety of real situations involving large-scale systems. Arthur Gelb writes in the Foreword that "It is our intent throughout to provide a simple and interesting picture of the central issues underlying modern estimation theory and practice. Heuristic, rather than theoretically elegant, arguments are used extensively, with emphasis on physical insights and key questions of practical importance." Numerous illustrative examples, many based on actual applications, have been interspersed throughout the text to lead the student to a concrete understanding of the theoretical material. The inclusion of problems with "built-in" answers at the end of each of the nine chapters further enhances the self-study potential of the text. After a brief historical prelude, the book introduces the mathematics underlying random process theory and state-space characterization of linear dynamic systems. The theory and practice of optimal estimation is them presented, including filtering, smoothing, and prediction. Both linear and non-linear systems, and continuous- and discrete-time cases, are covered in considerable detail. New results are described concerning the application of covariance analysis to non-linear systems and the connection between observers and optimal estimators. The final chapters treat such practical and often pivotal issues as suboptimal structure, and computer loading considerations. This book is an outgrowth of a course given by TASC at a number of US Government facilities. Virtually all of the members of the TASC technical staff have, at one time and in one way or another, contributed to the material contained in the work.
Nonlinear Lp Norm Estimation
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Author : Rene Gonin
language : en
Publisher: CRC Press
Release Date : 1989-02-10
Nonlinear Lp Norm Estimation written by Rene Gonin and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989-02-10 with Mathematics categories.
Lp-norm estimation in linear regression; The nonlinear l1-norm estimation problem; The nonlinear L OO-norm estimation proble; The nonlinear Lp-norm estimation problem; Statistical aspects of Lp-norm estimators; Application of Lp-norm estimation.