A gaussian function network for uncertainty propagation through nonlinear dynamical system

Puneet Singla, Tarunraj Singh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

10 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationSpace Flight Mechanics 2008 - Advances in the Astronautical Sciences, Proceedings of the AAS/AIAA Space Flight Mechanics Meeting
Pages851-864
Number of pages14
StatePublished - 2008
Event18th Annual Space Flight Mechanics Meeting - Galveston, TX, United States
Duration: Jan 27 2008Jan 31 2008

Publication series

NameAdvances in the Astronautical Sciences
Volume130 PART 1
ISSN (Print)0065-3438

Other

Other18th Annual Space Flight Mechanics Meeting
CountryUnited States
CityGalveston, TX
Period1/27/081/31/08

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science

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