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

This paper presents an 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 includes copies of 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.