TY - GEN
T1 - A gaussian function network for uncertainty propagation through nonlinear dynamical system
AU - Singla, Puneet
AU - Singh, Tarunraj
PY - 2008
Y1 - 2008
N2 - A Gaussian mixture model approach is proposed for accurate uncertainty propagation through a general nonlinear system. The transition probability density function, is approximated by a finite sum of Gaussian density functions whose parameters (mean and covariance) are propagated using linear propagation theory. Further, Fokker-Planck equation error is used as a feedback to adapt for the amplitude of different Gaussian components while solving a convex quadratic programming problem. The proposed method is applied to a variety of test problems in the open literature, and argued to be an excellent candidate for higher dimensional uncertainty propagation problems.
AB - A Gaussian mixture model approach is proposed for accurate uncertainty propagation through a general nonlinear system. The transition probability density function, is approximated by a finite sum of Gaussian density functions whose parameters (mean and covariance) are propagated using linear propagation theory. Further, Fokker-Planck equation error is used as a feedback to adapt for the amplitude of different Gaussian components while solving a convex quadratic programming problem. The proposed method is applied to a variety of test problems in the open literature, and argued to be an excellent candidate for higher dimensional uncertainty propagation problems.
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M3 - Conference contribution
AN - SCOPUS:60349127032
SN - 9780877035442
T3 - Advances in the Astronautical Sciences
SP - 851
EP - 864
BT - Space Flight Mechanics 2008 - Advances in the Astronautical Sciences, Proceedings of the AAS/AIAA Space Flight Mechanics Meeting
T2 - 18th Annual Space Flight Mechanics Meeting
Y2 - 27 January 2008 through 31 January 2008
ER -