Robust Kalman Filtering for Signals and Systems with Large Uncertainties

Klappentext

The Kalman Filter gives an optimal estimate of the state of the given process based on output measurements. The aim of this text is to cover the theory of robust state estimation for the case in which the process model contains significant uncertainties and non-linearities.

Inhalt

Continuous-time quadratic guaranteed cost filtering; discrete-time quadratic guaranteed cost filtering; continuous-time set valued state estimation and model validation; discrete-time set valued estimation and model validation; robust state estimation with discrete and continuous measurements; set valued state estimation with structured uncertainty; robust H-infinity filtering with structured uncertainty; robust fixed order H-infinity filtering; set valued state estimation for nonlinear uncertain systems; robust filtering applied to an induction motor.