A nonsmooth Kalman filter for state estimation of positioning stage based on sandwich model with backlash-like hysteresis

In this paper, a nonsmooth Kalman filtering (NKF) strategy is proposed for state estimation of macro-motion positioning stages with ball-screw-nut transmission mechanism. In this method, the characteristic of the positioning stage is described by so-called sandwich state-space model with backlash-like hysteresis. By considering the influence of random noise on positioning stage, based on the dynamic model with backlash-like hysteresis, a nonsmooth Kalman filter is proposed for state estimation of positioning stage in noisy environment. Moreover, a method of observability test for sandwich systems with backlash-like hysteresis is developed for observability check before the nonsmooth Kalman filter is implemented. Finally, the proposed NKF method is applied to a positioning stage for state estimation.