State Estimation of RC Filters using Unscented Kalman Filter

Abstract

This paper implements unscented Kalman filter (UKF) for output voltage estimation of RC low pass filter (LPF) and high pass filter (HPF). At first, the state space model has been obtained using Kirchhoff’s current law (KCL). The performance of UKF has been compared with extended Kalman filter (EKF). The simulation results validate the superiority of UKF over EKF as the estimation error is smaller using UKF as compared to the EKF method. As the UKF uses unscented transform (UT) and EKF uses Taylor series expansion for linearization purpose, linearization error is smaller in UKF as compared to EKF method. Also, UKF implementation has the advantage that it does not require Jacobian computation of nonlinear system model.