Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches

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9780471708582: Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches
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A bottom-up approach that enables readers to master and apply thelatest techniques in state estimation

This book offers the best mathematical approaches to estimating thestate of a general system. The author presents state estimationtheory clearly and rigorously, providing the right amount ofadvanced material, recent research results, and references toenable the reader to apply state estimation techniques confidentlyacross a variety of fields in science and engineering.

While there are other textbooks that treat state estimation, thisone offers special features and a unique perspective andpedagogical approach that speed learning:
* Straightforward, bottom-up approach begins with basic conceptsand then builds step by step to more advanced topics for a clearunderstanding of state estimation
* Simple examples and problems that require only paper and pen tosolve lead to an intuitive understanding of how theory works inpractice
* MATLAB(r)-based source code that corresponds to examples in thebook, available on the author's Web site, enables readers torecreate results and experiment with other simulation setups andparameters

Armed with a solid foundation in the basics, readers are presentedwith a careful treatment of advanced topics, including unscentedfiltering, high order nonlinear filtering, particle filtering,constrained state estimation, reduced order filtering, robustKalman filtering, and mixed Kalman/H? filtering.

Problems at the end of each chapter include both written exercisesand computer exercises. Written exercises focus on improving thereader's understanding of theory and key concepts, whereas computerexercises help readers apply theory to problems similar to onesthey are likely to encounter in industry. With its expert blend oftheory and practice, coupled with its presentation of recentresearch results, Optimal State Estimation is strongly recommendedfor undergraduate and graduate-level courses in optimal control andstate estimation theory. It also serves as a reference forengineers and science professionals across a wide array ofindustries.

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About the Author:

DAN SIMON, PhD, is an Associate Professor at Cleveland State University. Prior to this appointment, Dr. Simon spent fourteen years working for such firms as Boeing, TRW, and several smaller companies.

Review:

"This book is obviously written with care and reads very easily. Avery valuable resource for students, teachers, andpractitioners...highly recommended." (CHOICE, February2007)

"The dozens of helpful step-by-step examples, visualillustrations, and lists of exercises proposed at the end of eachchapter significantly facilitate a reader's understanding of thebook's content." (Computing Reviews.com, December 4,2006)

"About this title" may belong to another edition of this title.

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Book Description John Wiley & Sons Inc, United States, 2006. Hardback. Condition: New. 1. Auflage. Language: English. Brand new Book. 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. A solutions manual is available for instructors. 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. A solutions manual is available upon request from the Wiley editorial board. Seller Inventory # AAH9780471708582

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Book Description John Wiley & Sons Inc, United States, 2006. Hardback. Condition: New. 1. Auflage. Language: English. Brand new Book. 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. A solutions manual is available for instructors. 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. A solutions manual is available upon request from the Wiley editorial board. Seller Inventory # AAH9780471708582

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