Data-Based Identifiability and Observability Assessment for Nonlinear Control Systems Using the Profile Likelihood Method
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DOI: 10.25534/tuprints-00011713
Abstract: Abstract This paper introduces the profile likelihood method in order to assess simultaneously the parameter identifiability and the state observability for nonlinear dynamic state-space models with constant parameters. While a formal definition of a parameter’s… read more here.
Keywords: profile likelihood; identifiability; observability; using profile ... See more keywords