On simulating randomly driven dynamic systems

N. Jeremy Kasdin, Landis J. Stankievech

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


Much of modern estimation and control theory is based on dynamic models with random forcing terms. As long as these models are linear, the behavior of the system is well understood; in fact, the state space system can be solved exactly. In this paper we address the problem of simulating such systems such that the average properties of the simulation match those of the true system being modeled. We present previous results on Runge-Kutta methods for linear, stochastic state space systems and show how even these need to be treated carefully. We then discuss nonlinear stochastic models and how the two main types, Ito and Stratonovich, relate to the physical systems being considered. We present a Runge-Kutta type algorithm for simulating nonlinear stochastic systems and demonstrate the validity of the approach on a simple laboratory experiment.

Original languageEnglish (US)
Title of host publicationThe F. Landis Markley Astronautics Symposium - Advances in the Astronautical Sciences
Subtitle of host publicationProceedings of the American Astronautical Society F. Landis Markley Astronautics Symposium
Number of pages19
StatePublished - 2008
EventAmerican Astronautical Society F. Landis Markley Astronautics Symposium - Cambridge, MD, United States
Duration: Jun 29 2008Jul 2 2008

Publication series

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


OtherAmerican Astronautical Society F. Landis Markley Astronautics Symposium
Country/TerritoryUnited States
CityCambridge, MD

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science


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