Title :
A Discrete-Time Robust Extended Kalman Filter for Uncertain Systems With Sum Quadratic Constraints
Author :
Kallapur, Abhijit G. ; Petersen, Ian R. ; Anavatti, Sreenatha G.
Author_Institution :
Sch. of Aerosp., Univ. of New South Wales at the Australian Defence Force Acad., Canberra, ACT
fDate :
4/1/2009 12:00:00 AM
Abstract :
This technical note outlines the formulation of a novel discrete-time robust extended Kalman filter for uncertain systems with uncertainties described in terms of sum quadratic constraints. The robust filter is an approximate set-valued state estimator which is robust in the sense that it can handle modeling uncertainties in addition to exogenous noise. Riccati and filter difference equations are obtained as an approximate solution to a reverse-time optimal control problem defining the set-valued state estimator. In order to obtain a solution to the set-valued state estimation problem, the discrete-time system dynamics are modeled backwards in time.
Keywords :
Kalman filters; Riccati equations; difference equations; discrete time systems; nonlinear filters; optimal control; state estimation; uncertain systems; Riccati equations; discrete-time robust extended Kalman filter; discrete-time system dynamics; filter difference equations; reverse-time optimal control; set-valued state estimator; sum quadratic constraints; uncertain systems; Australia; Dynamic programming; Filters; Noise robustness; Nonlinear dynamical systems; Nonlinear systems; Optimal control; State estimation; Uncertain systems; Uncertainty; Extended Kalman filter (EKF); integral quadratic constant (IQC); sum quadratic constant (SQC);
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2008.2010962