State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties
State estimation techniques for centralized, distributed, and decentralized systems are studied. An easy-to-implement state estimation concept is introduced that generalizes and combines basic principles of Kalman filter theory and ellipsoidal calculus. By means of this method, stochastic and set-me...
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| 格式: | Online |
| 語言: | 英语 |
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KIT Scientific Publishing
2021
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| 主題: | |
| 在線閱讀: | 35025 |
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| _version_ | 1869529032871116800 |
|---|---|
| author | Noack, Benjamin |
| author_browse | Noack, Benjamin |
| author_facet | Noack, Benjamin |
| author_sort | Noack, Benjamin |
| collection | Directory of Open Access Books |
| description | State estimation techniques for centralized, distributed, and decentralized systems are studied. An easy-to-implement state estimation concept is introduced that generalizes and combines basic principles of Kalman filter theory and ellipsoidal calculus. By means of this method, stochastic and set-membership uncertainties can be taken into consideration simultaneously. Different solutions for implementing these estimation algorithms in distributed networked systems are presented. |
| format | Online |
| id | doab-20.500.12854ir-59976 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | KIT Scientific Publishing |
| publisherStr | KIT Scientific Publishing |
| record_format | ojs |
| spelling | doab-20.500.12854ir-599762023-12-20T18:40:51Z State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties Noack, Benjamin QA75.5-76.95 distributed estimation Kalman filter set-membership estimation Bayesian state estimation bic Book Industry Communication::U Computing & information technology::UY Computer science State estimation techniques for centralized, distributed, and decentralized systems are studied. An easy-to-implement state estimation concept is introduced that generalizes and combines basic principles of Kalman filter theory and ellipsoidal calculus. By means of this method, stochastic and set-membership uncertainties can be taken into consideration simultaneously. Different solutions for implementing these estimation algorithms in distributed networked systems are presented. 2021-02-12T04:28:40Z 2021-02-12T04:28:40Z 2019-07-30 20:02:00 2014 book 35025 18673813 9783731501244 https://directory.doabooks.org/handle/20.500.12854/59976 eng Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory image/jpeg Attribution-ShareAlike 4.0 International https://www.ksp.kit.edu/9783731501244 KIT Scientific Publishing 10.5445/KSP/1000036878 10.5445/KSP/1000036878 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783731501244 XVIII, 257 p. open access |
| spellingShingle | QA75.5-76.95 distributed estimation Kalman filter set-membership estimation Bayesian state estimation bic Book Industry Communication::U Computing & information technology::UY Computer science Noack, Benjamin State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties |
| title | State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties |
| title_full | State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties |
| title_fullStr | State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties |
| title_full_unstemmed | State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties |
| title_short | State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties |
| title_sort | state estimation for distributed systems with stochastic and set membership uncertainties |
| topic | QA75.5-76.95 distributed estimation Kalman filter set-membership estimation Bayesian state estimation bic Book Industry Communication::U Computing & information technology::UY Computer science |
| topic_facet | QA75.5-76.95 distributed estimation Kalman filter set-membership estimation Bayesian state estimation bic Book Industry Communication::U Computing & information technology::UY Computer science |
| url | 35025 |
| work_keys_str_mv | AT noackbenjamin stateestimationfordistributedsystemswithstochasticandsetmembershipuncertainties |