Nonlinear state and parameter estimation of spatially distributed systems
In this thesis two probabilistic model-based estimators are introduced that allow the reconstruction and identification of space-time continuous physical systems. The Sliced Gaussian Mixture Filter (SGMF) exploits linear substructures in mixed linear/nonlinear systems, and thus is well-suited for id...
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| Format: | Electronic Book Chapter |
| Language: | English |
| Published: |
KIT Scientific Publishing
2009
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| Series: | Karlsruhe Series on Intelligent Sensor-Actuator-Systems, Universität Karlsruhe / Intelligent Sensor-Actuator-Systems Laboratory
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| Subjects: | |
| Online Access: | DOAB: download the publication DOAB: description of the publication |
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| 020 | |a 9783866443709 | ||
| 040 | |a oapen |c oapen | ||
| 024 | 7 | |a 10.5445/KSP/1000011485 |c doi | |
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| 042 | |a dc | ||
| 100 | 1 | |a Sawo, Felix |4 auth | |
| 245 | 1 | 0 | |a Nonlinear state and parameter estimation of spatially distributed systems |
| 260 | |b KIT Scientific Publishing |c 2009 | ||
| 300 | |a 1 electronic resource (XI, 153 p. p.) | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 490 | 1 | |a Karlsruhe Series on Intelligent Sensor-Actuator-Systems, Universität Karlsruhe / Intelligent Sensor-Actuator-Systems Laboratory | |
| 506 | 0 | |a Open Access |2 star |f Unrestricted online access | |
| 520 | |a In this thesis two probabilistic model-based estimators are introduced that allow the reconstruction and identification of space-time continuous physical systems. The Sliced Gaussian Mixture Filter (SGMF) exploits linear substructures in mixed linear/nonlinear systems, and thus is well-suited for identifying various model parameters. The Covariance Bounds Filter (CBF) allows the efficient estimation of widely distributed systems in a decentralized fashion. | ||
| 540 | |a Creative Commons |f https://creativecommons.org/licenses/by-nc-nd/4.0/ |2 cc |4 https://creativecommons.org/licenses/by-nc-nd/4.0/ | ||
| 546 | |a English | ||
| 653 | |a sensor network | ||
| 653 | |a nonlinear estimation | ||
| 653 | |a distributed-parameter system | ||
| 856 | 4 | 0 | |a www.oapen.org |u https://www.ksp.kit.edu/9783866443709 |7 0 |z DOAB: download the publication |
| 856 | 4 | 0 | |a www.oapen.org |u https://directory.doabooks.org/handle/20.500.12854/54761 |7 0 |z DOAB: description of the publication |