A Comparative Analysis of Real-time state estimation using Kalman and Extended Kalman Filters for TRMS
Lakshmi Dutta, Dushmanta Kumar Das · 2018
The state estimation problem for the nonlinear system is a most important issue for industrial control application. It is also preferable that the estimation technique should be accurate and easily implementable. In the present work, we compare the performance of two estimation algorithm for state estimation of the Twin Rotor MIMO system (TRMS). Here, the Kalman filter (KF)and extended Kalman filter (EKF) are used for realtime state estimation for the system. It is observed that in both simulation and experimental result, that the performance of EKF is better than the KF in terms of robustness and root mean square error (RMSE) in state estimation.