Robust Guaranteed Cost State Estimation for Nonlinear Stochastic Uncertain Systems Via an IQC Approach

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^infin control theory and this leads to a nonlinear state estimator which gives an upper bound on the estimation error cost.