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Application Of Kalman Filter Technique For Optimal Use Of Time Series Information In Dynamic Optimization Problems
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Book Synopsis Application of Kalman-filter Technique for Optimal Use of Time-series Information in Dynamic Optimization Problems by : Keshav P. Vishwakarma
Download or read book Application of Kalman-filter Technique for Optimal Use of Time-series Information in Dynamic Optimization Problems written by Keshav P. Vishwakarma and published by . This book was released on 1970 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Application of Kalman-filter Technique for Optimal Use of Time-series Information in Dynamic Optimazation Problems by : Keshav P. Vishwakarma
Download or read book Application of Kalman-filter Technique for Optimal Use of Time-series Information in Dynamic Optimazation Problems written by Keshav P. Vishwakarma and published by . This book was released on 1970 with total page 17 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kalman Filtering with Real-Time Applications by : Charles K. Chui
Download or read book Kalman Filtering with Real-Time Applications written by Charles K. Chui and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filtering is an optimal state estimation process applied to a dynamic system that involves random perturbations. More precisely, the Kalman filter gives a linear, unbiased, and min imum error variance recursive algorithm to optimally estimate the unknown state of a dynamic system from noisy data taken at discrete real-time intervals. It has been widely used in many areas of industrial and government applications such as video and laser tracking systems, satellite navigation, ballistic missile trajectory estimation, radar, and fue control. With the recent development of high-speed computers, the Kalman filter has become more use ful even for very complicated real-time applications. lnspite of its importance, the mathematical theory of Kalman filtering and its implications are not well understood even among many applied mathematicians and engineers. In fact, most prac titioners are just told what the filtering algorithms are without knowing why they work so well. One of the main objectives of this text is to disclose this mystery by presenting a fairly thor ough discussion of its mathematical theory and applications to various elementary real-time problems. A very elementary derivation of the filtering equations is fust presented. By assuming that certain matrices are nonsingular, the advantage of this approach is that the optimality of the Kalman filter can be easily understood. Of course these assump tions can be dropped by using the more well known method of orthogonal projection usually known as the innovations approach.
Download or read book Kalman Filters written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-06-27 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Kalman Filters An algorithm that uses a series of measurements observed over time, including statistical noise and other inaccuracies, Kalman filtering is also known as linear quadratic estimation (LQE), and it produces estimates of unknown variables that tend to be more accurate than those that are based on a single measurement alone, by estimating a joint probability distribution over the variables for each timeframe. This is accomplished by estimating a joint probability distribution over the variables for each timeframe. Rudolf E. Kálmán, who was a significant contributor to the development of the theory behind the filter, is honored with the naming of the device. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Kalman filter Chapter 2: Weighted arithmetic mean Chapter 3: Multivariate random variable Chapter 4: Covariance Chapter 5: Covariance matrix Chapter 6: Expectation-maximization algorithm Chapter 7: Minimum mean square error Chapter 8: Recursive least squares filter Chapter 9: Linear-quadratic-Gaussian control Chapter 10: Extended Kalman filter (II) Answering the public top questions about kalman filters. (III) Real world examples for the usage of kalman filters in many fields. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of kalman filters. What is Artificial Intelligence Series The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field. The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.
Book Synopsis Kalman Filters by : Ginalber Luiz Serra
Download or read book Kalman Filters written by Ginalber Luiz Serra and published by BoD – Books on Demand. This book was released on 2018-02-21 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent issues on theory and practice of Kalman filters, with a comprehensive treatment of a selected number of concepts, techniques, and advanced applications. From an interdisciplinary point of view, the contents from each chapter bring together an international scientific community to discuss the state of the art on Kalman filter-based methodologies for adaptive/distributed filtering, optimal estimation, dynamic prediction, nonstationarity, robot navigation, global navigation satellite systems, moving object tracking, optical communication systems, and active power filters, among others. The theoretical and methodological foundations combined with extensive experimental explanation make this book a reference suitable for students, practicing engineers, and researchers in sciences and engineering.
Book Synopsis Kalman Filtering With Inequality Constraints for Turbofan Engine Health Estimation by :
Download or read book Kalman Filtering With Inequality Constraints for Turbofan Engine Health Estimation written by and published by . This book was released on 2003 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints (which may be based on physical considerations) are often neglected because they do not fit easily into the structure of the Kalman filter. This paper develops two analytic methods of incorporating state variable inequality constraints in the Kalman filter. The first method is a general technique of using hard constraints to enforce inequalities on the state variable estimates. The resultant filter is a combination of a standard Kalman filter and a quadratic programming problem. The second method uses soft constraints to estimate state variables that are known to vary slowly with time. (Soft constraints are constraints that are required to be approximately satis- fied rather than exactly satisfied.) The incorporation of state variable constraints increases the computational effort of the filter but significantly improves its estima- tion accuracy. The improvement is proven theoretically and shown via simulation results. The use of the algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate health parameters. The turbofan engine model con- tains 16 state variables, 12 measurements, and 8 component health parameters. It is shown that the new algorithms provide improved performance in this example over unconstrained Kalman filtering.
Book Synopsis Applications and Optimizations of Kalman Filter and Their Variants by : Asadullah Khalid
Download or read book Applications and Optimizations of Kalman Filter and Their Variants written by Asadullah Khalid and published by BoD – Books on Demand. This book was released on 2024-07-17 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applications and Optimizations of Kalman Filter and Their Variants is a comprehensive exploration of Kalman filters’ diverse applications and refined optimizations across various domains. It meticulously examines their role in microgrid management, offering adaptive estimation techniques for effective control strategies. The book then delves into distribution system state estimation, showcasing an innovative stochastic programming model using extended Kalman filters for reliable monitoring and control. In the realm of financial modeling, readers gain insights into how Kalman filters enhance trading strategies like pairs trading and partial co-integration, bridging finance and analytics. Moreover, the book discusses Kalman filter optimization, addressing challenges in object tracking and error reduction with techniques like dynamic stochastic approximation algorithms and M-robust estimates. With practical examples and interdisciplinary approaches, this book serves as a valuable resource for researchers, practitioners, and students looking to harness Kalman filter techniques for enhanced efficiency and accuracy across diverse fields.
Book Synopsis Restricted Kalman Filtering by : Adrian Pizzinga
Download or read book Restricted Kalman Filtering written by Adrian Pizzinga and published by Springer Science & Business Media. This book was released on 2012-07-25 with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: In statistics, the Kalman filter is a mathematical method whose purpose is to use a series of measurements observed over time, containing random variations and other inaccuracies, and produce estimates that tend to be closer to the true unknown values than those that would be based on a single measurement alone. This Brief offers developments on Kalman filtering subject to general linear constraints. There are essentially three types of contributions: new proofs for results already established; new results within the subject; and applications in investment analysis and macroeconomics, where the proposed methods are illustrated and evaluated. The Brief has a short chapter on linear state space models and the Kalman filter, aiming to make the book self-contained and to give a quick reference to the reader (notation and terminology). The prerequisites would be a contact with time series analysis in the level of Hamilton (1994) or Brockwell & Davis (2002) and also with linear state models and the Kalman filter – each of these books has a chapter entirely dedicated to the subject. The book is intended for graduate students, researchers and practitioners in statistics (specifically: time series analysis and econometrics).
Book Synopsis Approximate Kalman Filtering by : Guanrong Chen
Download or read book Approximate Kalman Filtering written by Guanrong Chen and published by World Scientific. This book was released on 1993 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Kalman filtering algorithm gives optimal (linear, unbiased and minimum error-variance) estimates of the unknown state vectors of a linear dynamic-observation system, under the regular conditions such as perfect data information; complete noise statistics; exact linear modeling; ideal well-conditioned matrices in computation and strictly centralized filtering.In practice, however, one or more of the aforementioned conditions may not be satisfied, so that the standard Kalman filtering algorithm cannot be directly used, and hence ?approximate Kalman filtering? becomes necessary. In the last decade, a great deal of attention has been focused on modifying and/or extending the standard Kalman filtering technique to handle such irregular cases. It has been realized that approximate Kalman filtering is even more important and useful in applications.This book is a collection of several tutorial and survey articles summarizing recent contributions to the field, along the line of approximate Kalman filtering with emphasis on both its theoretical and practical aspects.
Book Synopsis Data-Driven Prediction for Industrial Processes and Their Applications by : Jun Zhao
Download or read book Data-Driven Prediction for Industrial Processes and Their Applications written by Jun Zhao and published by Springer. This book was released on 2018-08-20 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.
Book Synopsis Kalman Filtering and Neural Networks by : Simon Haykin
Download or read book Kalman Filtering and Neural Networks written by Simon Haykin and published by John Wiley & Sons. This book was released on 2004-03-24 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: State-of-the-art coverage of Kalman filter methods for the design of neural networks This self-contained book consists of seven chapters by expert contributors that discuss Kalman filtering as applied to the training and use of neural networks. Although the traditional approach to the subject is almost always linear, this book recognizes and deals with the fact that real problems are most often nonlinear. The first chapter offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended Kalman filter. Other chapters cover: An algorithm for the training of feedforward and recurrent multilayered perceptrons, based on the decoupled extended Kalman filter (DEKF) Applications of the DEKF learning algorithm to the study of image sequences and the dynamic reconstruction of chaotic processes The dual estimation problem Stochastic nonlinear dynamics: the expectation-maximization (EM) algorithm and the extended Kalman smoothing (EKS) algorithm The unscented Kalman filter Each chapter, with the exception of the introduction, includes illustrative applications of the learning algorithms described here, some of which involve the use of simulated and real-life data. Kalman Filtering and Neural Networks serves as an expert resource for researchers in neural networks and nonlinear dynamical systems.
Book Synopsis Advanced Kalman Filtering, Least-Squares and Modeling by : Bruce P. Gibbs
Download or read book Advanced Kalman Filtering, Least-Squares and Modeling written by Bruce P. Gibbs and published by John Wiley & Sons. This book was released on 2011-03-29 with total page 559 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended primarily as a handbook for engineers who must design practical systems. Its primary goal is to discuss model development in sufficient detail so that the reader may design an estimator that meets all application requirements and is robust to modeling assumptions. Since it is sometimes difficult to a priori determine the best model structure, use of exploratory data analysis to define model structure is discussed. Methods for deciding on the “best” model are also presented. A second goal is to present little known extensions of least squares estimation or Kalman filtering that provide guidance on model structure and parameters, or make the estimator more robust to changes in real-world behavior. A third goal is discussion of implementation issues that make the estimator more accurate or efficient, or that make it flexible so that model alternatives can be easily compared. The fourth goal is to provide the designer/analyst with guidance in evaluating estimator performance and in determining/correcting problems. The final goal is to provide a subroutine library that simplifies implementation, and flexible general purpose high-level drivers that allow both easy analysis of alternative models and access to extensions of the basic filtering. Supplemental materials and up-to-date errata are downloadable at http://booksupport.wiley.com.
Download or read book Kalman Filter written by Víctor M. Moreno and published by BoD – Books on Demand. This book was released on 2009-04-01 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: The aim of this book is to provide an overview of recent developments in Kalman filter theory and their applications in engineering and scientific fields. The book is divided into 24 chapters and organized in five blocks corresponding to recent advances in Kalman filtering theory, applications in medical and biological sciences, tracking and positioning systems, electrical engineering and, finally, industrial processes and communication networks.
Book Synopsis Theory and Applications of Kalman Filtering by : Cornelius T. Leondes
Download or read book Theory and Applications of Kalman Filtering written by Cornelius T. Leondes and published by . This book was released on 1970 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contents: Linear estimation theory; Further comments on the derivation of Kalman filters; Computational techniques in Kalman filtering; Modeling errors in Kalman filters; Suboptimal Kalman filter techniques; Comparison of Kalman, Bayesian and maximum likelihood estimation techniques; Nonlinear filtering and comparison with Kalman filtering; Linear smoothing techniques (post-flight data analysis); Nonlinear smoothing techniques; General questions on Kalman filtering in navigation systems; Application of Kalman filtering theory to augmented inertial navigation systems; Application of Kalman filtering to Baro/inertial height systems; Application of Kalman filtering to the C-5 guidance and control system; Application of Kalman filtering techniques to the Apollo program; Some applications of Kalman filtering in space guidance; Application of Kalman filtering for the alighnment of carrier aircraft inertial navigation systems; Navigation at sea using the invariants form of Kalman filtering; Marine applications of Kalman filtering; Optimal use of redundant information in an inertial navigation; Application of Kalman filtering techniques to strapdown system initia-alignment; and A Kalman filter augmented marine navigation system.
Book Synopsis Kalman Filtering by : Mohinder S. Grewal
Download or read book Kalman Filtering written by Mohinder S. Grewal and published by Prentice Hall. This book was released on 1993 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thorough exploration of the theory and application of Kalman filtering to real-world situations. *book contains a floppy disk with C++ and MATLAB algorithms. *offers a heuristic treatment of essential material. *includes many often ignored design and implementation techniques. *explores the appropriate numerical methods for reliable implementation. *contains a variety of examples and problems taken from real-world application situations - e.g., modelling of gyros, accelerometers, inertial navigation; freeway traffic model; a harmonic oscillator; radar tracking; Global Positioning System (GPS) aided Inertial Navigation System (INS). *includes companion software to solve large dimension problems in the text.
Book Synopsis Scientific and Technical Aerospace Reports by :
Download or read book Scientific and Technical Aerospace Reports written by and published by . This book was released on 1995 with total page 704 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Kalman Filtering by : Mohinder S. Grewal
Download or read book Kalman Filtering written by Mohinder S. Grewal and published by Wiley-Interscience. This book was released on 2001-01-16 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: Disk contains: Demonstation programs and source code in MATLAB for algorithms in text.
