Suboptimal filter for continuous‐time linear systems with unknown parameters

The filtering problem for continuous-time linear systems with unknown parameters is considered. A new suboptimal filter is herein proposed. It is based on the optimal mean-square linear combination of the local Kalman filters. In contrast to the optimal weights, the suboptimal weights do not depend on current observations; thus, the proposed filter can easily be implemented in real-time. Examples demonstrate high accuracy and efficiency of the suboptimal filter.