Petersen, Ian R.2026-07-032026-07-0314244090209781424409020ORCID:/0000-0003-4856-9450/work/219177665https://hdl.handle.net/1885/733812473This 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.This work was supported by the Australian Research Council.6en200710.1109/IDC.2007.37451834548832236