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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| Auteur principal: | |
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| Format: | Électronique Chapitre de livre |
| Langue: | anglais |
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KIT Scientific Publishing
2014
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| Collection: | Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory
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| Sujets: | |
| Accès en ligne: | DOAB: download the publication DOAB: description of the publication |
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| Résumé: | 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. |
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| Description matérielle: | 1 electronic resource (XVIII, 257 p. p.) |
| ISBN: | KSP/1000036878 9783731501244 |
| Accès: | Open Access |