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KALMAN-BUCY FILTERING FOR SINGULAR STOCHASTIC DIFFERENTIAL SYSTEMS
A. Germani1,2 C. Manes1,2 P. Palumbo2
1 Dipartimento di Ingegneria Elettrica
Università degli Studi dell’Aquila,
Monteluco di Roio, 67040 L’Aquila, Italy
e-mail: {germani,manes}@ing.univaq.it
2 Istituto di Analisi dei Sistemi e Informatica
IASI-CNR, Viale Manzoni 30, 00185 Roma, Italy
e-mail: palumbo@iasi.rm.cnr.it
This work investigates the problem of state estimation for singular stochastic differential systems. A Kalman-Bucy-like filter is proposed, based on a suitable decomposition of the descriptor vector into two components. The first one is expressed as a function of the observation, and therefore does not need to be estimated, while the second component is described by a regular linear stochastic system and can be estimated by a Kalman-Bucy filter. Numerical simulations are presented on the case of a stochastic system with an unknown input, modeled as a singular system.
Keywords: descriptor systems, singular systems, Kalman-Bucy filtering, stochastic systems, state estimation
Session slot T-Tu-A07: Linear and Nonlinear Filtering/Area code 3d : Stochastic Systems
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