State Observation with Guaranteed Confidence Regions Through Sign Perturbed Sums
Sprache des Vortragstitels:
Englisch
Original Tagungtitel:
54th IEEE Conference on Decision and Control
Sprache des Tagungstitel:
Englisch
Original Kurzfassung:
Standard state estimation approaches do not provide
guaranteed confidence regions for finite data amounts.
For some applications, in particular safety critical ones, this
can be of interest. In this paper, we suggest a method to
construct a moving horizon state estimator (MHE) able to
provide confidence regions (CR) of the state estimate with
exact probability under mild assumptions on the noise. To
do so a novel algorithm called sign perturbed sums (SPS), as
presented by B.Cs. Csaji et al. in [4], is combined with a MHE
approach. The paper develops the idea for single input single
output (SISO) linear time invariant (LTI) state-space systems
and uses simulations and a comparison to results obtained in
the standard way to confirm the potential of the method.
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