Research of fuzzy adaptive filter in the problem sins

Abstract

A modified strong tracking unscented Kaiman filter nonlinear dynamical systems is proposed. A matrix of the suboptimal scaling factor is introduced into the prediction covariance to ensure stability and smoothness of the estimate in case of uncertainty of the process model. It is shown that the use of a fuzzy algorithm to adjust the softening coefficient in real time avoids the loss of accuracy in the segments in which the process model is defined. As a result of modeling, it was found that the proposed fuzzy filter has good smoothness of estimation and high accuracy.