Automatica, Vol.48, No.10, 2494-2501, 2012
Optimal H-2 filtering for a class of linear stochastic systems with sampling
This paper presents a Kalman-type filtering problem for a class of linear continuous-time stochastic systems with state-dependent noise and sampled measurements. The admissible class of filters is represented using dynamic models with finite jumps. Then an H-2 index is defined and computed for the resulting system with jumps. It is proved that the optimal H-2 filter depends on the stabilizing solution of a specific Riccati-type equation. A numerical example illustrates the theoretical developments. (c) 2012 Elsevier Ltd. All rights reserved.