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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Evolutionary Optimization Algorithms: Biologically Inspiredand Population-Based Approaches to Computer Intelligence is anideal text for advanced undergraduate students, graduate students,and professionals involved in engineering and computer science.

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Additional Information

Publisher
John Wiley & Sons
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Published on
Jun 19, 2006
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Pages
552
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ISBN
9780470045336
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Best For
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Language
English
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Genres
Technology & Engineering / Electrical
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Content Protection
This content is DRM protected.
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A clear and lucid bottom-up approach to the basic principlesof evolutionary algorithms

Evolutionary algorithms (EAs) are a type of artificialintelligence. EAs are motivated by optimization processes that weobserve in nature, such as natural selection, species migration,bird swarms, human culture, and ant colonies.

This book discusses the theory, history, mathematics, andprogramming of evolutionary optimization algorithms. Featuredalgorithms include genetic algorithms, genetic programming, antcolony optimization, particle swarm optimization, differentialevolution, biogeography-based optimization, and many others.

Evolutionary Optimization Algorithms:

Provides a straightforward, bottom-up approach that assists thereader in obtaining a clear—but theoreticallyrigorous—understanding of evolutionary algorithms, with anemphasis on implementationGives a careful treatment of recently developedEAs—including opposition-based learning, artificial fishswarms, bacterial foraging, and many others— and discussestheir similarities and differences from more well-establishedEAsIncludes chapter-end problems plus a solutions manual availableonline for instructorsOffers simple examples that provide the reader with anintuitive understanding of the theoryFeatures source code for the examples available on the author'swebsiteProvides advanced mathematical techniques for analyzing EAs,including Markov modeling and dynamic system modeling

Evolutionary Optimization Algorithms: Biologically Inspiredand Population-Based Approaches to Computer Intelligence is anideal text for advanced undergraduate students, graduate students,and professionals involved in engineering and computer science.

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