Performance Comparison of Extended Kalman Filter and Unscented Kalman Filter for the Control Moment Gyroscope Inverted Pendulum

This paper investigates the problem of nonlinear state estimation for control moment gyroscope (CMG) inverted pendulum. The dynamics of CMG inverted pendulum result into stiff nonlinearities and are included here. Both Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF) algorithms are utilized for state estimation to investigate their effectiveness. The computer simulations are included for comparison of the two algorithms. There are inherent difficulties in state estimation for systems with stiff nonlinearities. In this research, the results show that EKF performs far better than UKF in most cases for this system. However, this is an attempt to explore the nonlinear estimation problem for this challenging system.