State Estimation for Distributed Systems with Stochastic and Set-membership Uncertainties
Dissertationsschrift
(Sprache: Englisch)
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...
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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.
Klappentext zu „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-membership uncertainties can be taken into consideration simultaneously. Different solutions for implementing these estimation algorithms in distributed networked systems are presented.
Bibliographische Angaben
- Autor: Benjamin Noack
- 2014, XVIII, 289 Seiten, mit Abbildungen, Maße: 14,8 x 21 cm, Kartoniert (TB), Englisch
- Verlag: KIT Scientific Publishing
- ISBN-10: 3731501244
- ISBN-13: 9783731501244
Sprache:
Englisch
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