The unscented Kalman filter for the sandwich system with hysteresis

Hysteresis is a non-smooth nonlinearity with multi-valued mapping. As the practical systems are usually disturbed by stochastic noise, the noise suppression is one of the important issues in engineering. In this paper, the Unscented Kalman filter(UKF) is proposed to handle the state estimation for sandwich systems with hysteresis. The UKF approximates the probability density resulting from the non-linear transformation of a random variable instead of approximating the nonlinear functions with a Taylor series expansion. Then, the UKF algorithm is applied to the estimation of state of the model. Afterwards, a simulation example is presented to evaluate the proposed scheme.