Optimal State Estimation

Optimal State Estimation

Author: Dan Simon

Publisher: John Wiley & Sons

ISBN: 9780470045336

Category: Technology & Engineering

Page: 552

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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.
Optimal State Estimation
Language: en
Pages: 552
Authors: Dan Simon
Categories: Technology & Engineering
Type: BOOK - Published: 2006-06-19 - Publisher: John Wiley & Sons

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,
Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control
Language: en
Pages: 366
Authors: Ch. Venkateswarlu, Rama Rao Karri
Categories: Computers
Type: BOOK - Published: 2022-01-31 - Publisher: Elsevier

Optimal State Estimation for Process Monitoring, Fault Diagnosis and Control presents various mechanistic model based state estimators and data-driven model based state estimators with a special emphasis on their development and applications to process monitoring, fault diagnosis and control. The design and analysis of different state estimators are highlighted with
Optimal and Robust State Estimation
Language: en
Pages: 484
Authors: Yuriy S. Shmaliy, Shunyi Zhao
Categories: Technology & Engineering
Type: BOOK - Published: 2022-08-02 - Publisher: John Wiley & Sons

A unified and systematic theoretical framework for solving problems related to finite impulse response (FIR) estimate Optimal and Robust State Estimation: Finite Impulse Response (FIR) and Kalman Approaches is a comprehensive investigation into batch state estimators and recursive forms. The work begins by introducing the reader to the state estimation
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Language: en
Pages: 716
Authors: Robert F. Stengel
Categories: Mathematics
Type: BOOK - Published: 1994-09-20 - Publisher: Courier Corporation

"An excellent introduction to optimal control and estimation theory and its relationship with LQG design. . . . invaluable as a reference for those already familiar with the subject." — Automatica. This highly regarded graduate-level text provides a comprehensive introduction to optimal control theory for stochastic systems, emphasizing application of
Partially Observed Markov Decision Processes
Language: en
Pages:
Authors: Vikram Krishnamurthy
Categories: Technology & Engineering
Type: BOOK - Published: 2016-03-21 - Publisher: Cambridge University Press

Covering formulation, algorithms, and structural results, and linking theory to real-world applications in controlled sensing (including social learning, adaptive radars and sequential detection), this book focuses on the conceptual foundations of partially observed Markov decision processes (POMDPs). It emphasizes structural results in stochastic dynamic programming, enabling graduate students and researchers