Abstract
An online modelified Kalman filtering (MKF) algorithm for the parameter identification of sandwich systems with dead zone is proposed in this paper. With the switch functions introduced to represent the effect of dead zone, the pseudo-linear model with separated parameters to describe the sandwich system with dead zone is obtained. On account of the modeling residual is the Gaussian white noise sequence, a stochastic state space model is constructed. Then, the MKF algorithm is applied to the estimation of parameters of the model. Afterwards, a simulation example is presented to evaluate the proposed scheme.
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