Implementation of the unscented transformation with low rank approximation in uncertainty analysis during large-break loss of coolant accident
Sign Up to like & getrecommendations! Published in 2020 at "Annals of Nuclear Energy"
DOI: 10.1016/j.anucene.2020.107614
Abstract: Abstract The Low Rank Approximation (LRA) and Unscented Transform (UT) are integrated to produce a new algorithm having the capability to decrease the time required for the uncertainty quantification during Loss of coolant accident (LOCA)… read more here.
Keywords: coolant accident; sigma points; rank approximation; low rank ... See more keywords
Robust cubature Kalman filter based on variational Bayesian and transformed posterior sigma points error.
Sign Up to like & getrecommendations! Published in 2019 at "ISA transactions"
DOI: 10.1016/j.isatra.2018.11.005
Abstract: An improved robust cubature Kalman filter (RCKF) based on variational Bayesian (VB) and transformed posterior sigma points error is proposed in this paper, which not only retains the robustness of RCKF, but also exhibits adaptivity… read more here.
Keywords: transformed posterior; sigma; posterior sigma; points error ... See more keywords
Particle-filtering-based failure prognosis via sigma-points: Application to Lithium-Ion battery State-of-Charge monitoring
Sign Up to like & getrecommendations! Published in 2017 at "Mechanical Systems and Signal Processing"
DOI: 10.1016/j.ymssp.2016.08.029
Abstract: Abstract This paper presents a novel prognostic method that allows a proper characterization of the uncertainty associated with the evolution in time of nonlinear dynamical systems. The method assumes a state-space representation of the system,… read more here.
Keywords: state; filtering based; prognosis; sigma points ... See more keywords