Fuzzy dynamic model based state estimator
J.R. Layne, Kevin M. Passino · 2002
Systems containing uncertainty are traditionally analyzed with probabilistic methods. However, for nonlinear, non-Gaussian systems solutions can sometimes be very difficult to obtain. The focus of this research is to determine if in such cases fuzzy dynamic systems models may provide an alternative approach that more easily leads us to a good solution. In this article, we present a fuzzy estimator whose system model is a fuzzy dynamic system. We show that for the linear, Gaussian case the fuzzy estimator produces the same result as the Kalman filter.