State Estimation for Nonlinear Continuous–Discrete Stochastic Systems Numerical Aspects and Implementation Issues /
This book addresses the problem of accurate state estimation in nonlinear continuous-time stochastic models with additive noise and discrete measurements. Its main focus is on numerical aspects of computation of the expectation and covariance in Kalman-like filters rather than on statistical propert...
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| Główni autorzy: | , |
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| Format: | Elektroniczne E-book |
| Język: | angielski |
| Wydane: |
Cham :
Springer International Publishing : Imprint: Springer,
2024.
|
| Wydanie: | 1st ed. 2024. |
| Seria: | Studies in Systems, Decision and Control,
539 |
| Hasła przedmiotowe: | |
| Dostęp online: | https://doi.org/10.1007/978-3-031-61371-5 |
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| 100 | 1 | |a Kulikov, Gennady Yu. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a State Estimation for Nonlinear Continuous–Discrete Stochastic Systems |h [electronic resource] : |b Numerical Aspects and Implementation Issues / |c by Gennady Yu. Kulikov, Maria V. Kulikova. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Cham : |b Springer International Publishing : |b Imprint: Springer, |c 2024. | |
| 300 | |a 1 online resource (XXI, 798 p. 60 illus.). | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
| 341 | 0 | |b Use of color is not sole means of conveying information |2 onix | |
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| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a Studies in Systems, Decision and Control, |x 2198-4190 ; |v 539 | |
| 505 | 0 | |a Numerical Integration Methods for Ordinary Differential Equations -- Kalman Filtering for Linear Stochastic Modeling -- Extended Kalman Filtering for Nonlinear Stochastic Modeling -- Unscented Kalman Filtering for Nonlinear Stochastic Modeling -- Cubature Kalman Filtering for Nonlinear Stochastic Modeling -- Kalman-Like Filtering for Stiff Stochastic Modeling. | |
| 520 | |a This book addresses the problem of accurate state estimation in nonlinear continuous-time stochastic models with additive noise and discrete measurements. Its main focus is on numerical aspects of computation of the expectation and covariance in Kalman-like filters rather than on statistical properties determining a model of the system state. Nevertheless, it provides the sound theoretical background and covers all contemporary state estimation techniques beginning at the celebrated Kalman filter, including its versions extended to nonlinear stochastic models, and till the most advanced universal Gaussian filters with deterministically sampled mean and covariance. In particular, the authors demonstrate that, when applying such filtering procedures to stochastic models with strong nonlinearities, the use of adaptive ordinary differential equation solvers with automatic local and global error control facilities allows the discretization error—and consequently the state estimation error—to be reduced considerably. For achieving that, the variable-stepsize methods with automatic error regulation and stepsize selection mechanisms are applied to treating moment differential equations arisen. The implemented discretization error reduction makes the self-adaptive nonlinear Gaussian filtering algorithms more suitable for application and leads to the novel notion of accurate state estimation. The book also discusses accurate state estimation in mathematical models with sparse measurements. Of special interest in this regard, it provides a means for treating stiff stochastic systems, which often encountered in applied science and engineering, being exemplified by the Van der Pol oscillator in electrical engineering and the Oregonator model of chemical kinetics. Square-root implementations of all Kalman-like filters considered and explored in this book for state estimation in Ill-conditioned continuous–discrete stochastic systems attract the authors’ particular attention. This book covers both theoretical and applied aspects of numerical integration methods, including the concepts of approximation, convergence, stiffness as well as of local and global errors, suitably for applied scientists and engineers. Such methods serve as a basis for the development of accurate continuous–discrete extended, unscented, cubature and many other Kalman filtering algorithms, including the universal Gaussian methods with deterministically sampled expectation and covariance as well as their mixed-type versions. . | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Control engineering. | |
| 650 | 0 | |a System theory. | |
| 650 | 0 | |a Control theory. | |
| 650 | 0 | |a Signal processing. | |
| 650 | 1 | 4 | |a Control and Systems Theory. |
| 650 | 2 | 4 | |a Systems Theory, Control. |
| 650 | 2 | 4 | |a Digital and Analog Signal Processing. |
| 700 | 1 | |a Kulikova, Maria V. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
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| 776 | 0 | 8 | |i Printed edition: |z 9783031613708 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031613722 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031613739 |
| 830 | 0 | |a Studies in Systems, Decision and Control, |x 2198-4190 ; |v 539 | |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-61371-5 |
| 912 | |a ZDB-2-SMA | ||
| 912 | |a ZDB-2-SXMS | ||
| 950 | |a Mathematics and Statistics (SpringerNature-11649) | ||
| 950 | |a Mathematics and Statistics (R0) (SpringerNature-43713) | ||