Optimal filtering for uncertain linear stochastic systems

— This paper presents the optimal joint filtering and parameter identification problem for uncertain linear stochastic systems with unknown parameters in both state and observation equations, where the unknown parameters are considered Wiener processes. The original problem is reduced to the filtering problem for an extended state vector that incorporates parameters as additional states. The resulting filtering system is polynomial in state and linear in observations. The obtained optimal filter for the extended state vector also serves as the optimal identifier for the unknown parameters. Performance of the designed optimal state filter and parameter identifier is verified for both, positive and negative, parameter values.

• Type: Conference
• Year: 2009
• Where: CDC
• Authors: Michael V. Basin, Alexander G. Loukianov, Miguel Hernandez-Gonzalez
• Keywords: CDC 2009, Control Systems, Extended State Vector, Parameter, Unknown Parameters