Kalman Filter with Disturbance Estimation (KFD)

Abstract

The Kalman filter that includes disturbance estimation may be helpful if the effect of noise is significant and the time constant T in disturbance observer must be very long to solve the noise problem. This chapter introduces the Kalman filter using an extended system that incorporates the disturbance as a state variable. This is called as “Kalman filter with disturbance estimation”. A typical Kalman filter seeks an optimal estimate at each control cycle, and the Kalman gain value also changes, but once it converges, the gain value is almost constant. It should be less computationally expensive to use a stationary Kalman filter with a constant Kalman gain in such a case. A stationary Kalman filter with disturbance estimation using position observation is designed as a servo system with the cart model. Known state estimation methods for nonlinear systems include extended Kalman filter and unscented Kalman filter.