Simultaneous Estimation of Nonlinear Systems Driven by Unknown Nonlinear Actuator Using Unscented Kalman Filter (UKF)

Abstract

In this study, it is considered to estimate state of a known nonlinear plant with input from an unknown nonlinear actuator. To estimate nonlinear systems, a mathematical model which accurately describes the system is required. So, it is necessary to take into account the unknown nonlinearity of the actuator. We propose an estimation method of state and input from the unknown actuator using simultaneous estimation by UKF (Unscented Kalman Filter). Using this method, we can treat the unknown nonlinearity as estimation problem of unknown parameters. Effectiveness of the proposed method is shown by numerical experiments.