State Estimation of RC Filters using Unscented Kalman Filter
Amit Kumar Gautam1, Sudipta Majumdar2

1Amit Kumar Gautam, Senior Research Scholar, Department of Electronics and Communication Engineering, Delhi Technological University, India.
2Sudipta Majumdar, Assistant Professor, Department of Electronics and Communication Engineering Delhi Technological University, India.
Manuscript received on June 10, 2020. | Revised Manuscript received on June 25, 2020. | Manuscript published on July 10, 2020. | PP: 91-96 | Volume-9 Issue-9, July 2020 | Retrieval Number: 100.1/ijitee.I7512078919 | DOI: 10.35940/ijitee.I7512.079920
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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. 
Keywords:  Extended Kalman filter, RC filter, State space model, Unscented Kalman filter.
Scope of the Article: Concrete Structures