Set-membership Nonlinear Filtering with Second-order Information
نویسندگان
چکیده
In this paper, we develop a numerically efficient scheme for setmembership prediction and filtering for discrete-time nonlinear systems, that takes into explicit account the effects of nonlinearities via local second-order information. The filtering scheme is based on a classical prediction/update recursion that requires at each step the solution of a convex semidefinite optimization problem. The technical results discussed in the paper build upon the recently developed paradigm of uncertain linear equations (ULE) and semidefinite relaxations. Copyright c ©2005 IFAC
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