A Novel Approach to the Identification of Exogenous Input of Stochastic Systems Using Pseudomeasurement

Abstract

In this paper, a novel approach to identify an unknown parameter vector of the exogenous input to a class of stochastic linear systems is proposed. The key of the approach is to introduce an additional information about the unknown parameter vector which is called the pseudomeasurement. Augmenting this pseudomeasurement with the original observation data, the identification of unknown vector as well as the state estimation is performed. The efficacy of the proposed approach is confirmed by simulation studies.