Simultaneous Identification of Unknown System Matrix and Exogenous Input of Linear Stochastic Systems via Pseudomeasurement Approach

Abstract

In this paper, a method of simultaneous identification of the unknown parameters involved in the system matrix and unknown magnitude of suddenly discharged exogenous input is proposed for a class of linear stochastic systems using the idea of pseudomeasurement which has been developed extensively by the authors. The principal attack is to augment the pseudomeasurements with the original observation process and construct the Kalman filter. Numerical examples are presented to show the efficacy of the proposed approach.