Minimax Performance Limits for Multiple-Model Estimation
arxiv(2023)
摘要
This article concerns the performance limits of strictly causal state
estimation for linear systems with fixed, but uncertain, parameters belonging
to a finite set. In particular, we provide upper and lower bounds on the
smallest achievable gain from disturbances to the point-wise estimation error.
The bounds rely on forward and backward Riccati recursions -- one forward
recursion for each feasible model and one backward recursion for each pair of
feasible models. We give simple examples where the lower and upper bounds are
tight.
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