On maximum likelihood identification of errors-in-variables models
Sign Up to like & getrecommendations! Published in 2017 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2017.08.634
Abstract: Abstract In this paper, we revisit maximum likelihood methods for identification of errors-in-variables systems. We assume that the system admits a parametric description, and that the input is a stochastic ARMA process. The cost function… read more here.
Keywords: errors variables; maximum likelihood; variables models; likelihood identification ... See more keywords
Frequency Domain Maximum Likelihood Identification With Gaussian Input–Output Uncertainty
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DOI: 10.1109/lcsys.2019.2922063
Abstract: This letter deals with the identification of dynamical systems corrupted by additive and independent identically distributed Gaussian noise sources when the noise-free-input is an arbitrary signal. We review two stochastic models: 1) the errors-in-variables (EIV)… read more here.
Keywords: identification gaussian; maximum likelihood; input; domain maximum ... See more keywords
Maximum Likelihood Identification of Linear Models With Integrating Disturbances for Offset-Free Control
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DOI: 10.1109/tac.2025.3547607
Abstract: This article addresses the maximum likelihood identification of models for offset-free model predictive control, where linear time-invariant models are augmented with (fictitious) uncontrollable integrating modes, called integrating disturbances. The states and disturbances are typically estimated… read more here.
Keywords: likelihood identification; control; offset free; integrating disturbances ... See more keywords