Open AccessClosed-Loop Adaptive Monte Carlo Framework for Uncertainty Forecasting in Nonlinear Dynamic Systems
Author(s) -
Chao Yang,
Mrinal Kumar
Publication year - 2019
Publication title -
journal of guidance, control, and dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.573
H-Index - 143
eISSN - 1533-3884
pISSN - 0731-5090
DOI - 10.2514/1.g003853
Subject(s) - monte carlo method , nonlinear system , computer science , particle filter , representation (politics) , uncertainty quantification , mathematical optimization , probability density function , importance sampling , control theory (sociology) , sampling (signal processing) , mathematics , statistics , physics , kalman filter , control (management) , quantum mechanics , artificial intelligence , filter (signal processing) , machine learning , politics , political science , law , computer vision