Robust guaranteed cost state estimation for nonlinear stochastic uncertain systems via an IQC approach
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Petersen, Ian R.
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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.
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Conference Proceedings of 2007 Information, Decision and Control, IDC
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