Stochastic nonlinear minimax filtering in continuous-time
Date
2001Source
Proceedings of the IEEE Conference on Decision and ControlVolume
3Issue
Journal ArticlePages
2520-2525Google Scholar check
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This paper discusses nonlinear stochastic minimax games in which the minimizing player is the state estimate while the maximizing players are square-integrable stochastic disturbances. A pathwise optimization method is considered, and an information state is introduced as in [1], which is governed by a second-order Hamilton-Jacobi-Bellman (HJB) equation. The HJB equation is subsequently employed to characterize the dissipation properties of the estimator error with respect to the stochastic disturbances, and to introduce a certainty equivalence estimator.