Robust guaranteed cost state estimation for nonlinear stochastic uncertain systems via an IQC approach

Abstract

This paper presents a new approach to robust nonlinear state estimation based on the use of Integral Quadratic Constraints and minimax LQG control. The approach involves a class of state estimators which include copies on the system nonlinearities in the state estimator. The nonlinearities being considered are those which satisfy a certain global Lipschitz condition. The linear part of the state estimator is synthesized using minimax LQG control theory which is closely related to H∞ control theory and this leads to a nonlinear state estimator which gives an upper bound on the estimation error cost.