Identification of Unknown Exogenous Input to Stochastic Linear Systems Using Pseudomeasurements

Abstract

A joint method is proposed for estimating the systems state and identifying the unknown exogenous input to the stochastic dynamical systems by introducing an idea of pseudomeasurement. Both state estimation and parameter identification are processed by the Kalman filter, incorporating the pseudomeasurements. As unknown exogenous input, two kind of inputs-stepwise and impulse inputs-are investigated, and several simulation studies are presented in order to show the efficacy of introducing the pseudomeasurements.