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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| Format: | eBook |
| Language: | English |
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KIT Scientific Publishing
2014
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| Series: | Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory
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| Collection: | Directory of Open Access Books - Collection details see MPG.ReNa |
| Summary: | 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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| Item Description: | Creative Commons (cc), https://creativecommons.org/licenses/by-sa/4.0/ |
| Physical Description: | 1 electronic resource (XVIII, 257 p. p.) |
| ISBN: | 9783731501244 1000036878 |