Moment propagation of discrete-time stochastic polynomial systems using truncated carleman linearization

S Pruekprasert, T Takisaka, C Eberhart, A Cetinkaya… - IFAC-PapersOnLine, 2020 - Elsevier
We propose a method to compute an approximation of the moments of a discrete-time
stochastic polynomial system. We use the Carleman linearization technique to transform this …

Moment propagation of polynomial systems through Carleman linearization for probabilistic safety analysis

S Pruekprasert, J Dubut, T Takisaka, C Eberhart… - Automatica, 2024 - Elsevier
We develop a method to approximate the moments of a discrete-time stochastic polynomial
system. Our method is built upon Carleman linearization with truncation. Specifically, we …

Approximate linear minimum variance filters for continuous-discrete state space models: convergence and practical adaptive algorithms

JC Jimenez - IMA Journal of Mathematical Control and …, 2019 - academic.oup.com
In this article, approximate linear minimum variance (LMV) filters for continuous-discrete
state space models are introduced. The filters are derived from a wide class of recursive …

Direct computation of nth-order correlations of the solution of a non-linear stochastic equation

A Saïdi, J Dušek - The Quarterly Journal of Mechanics and …, 2023 - academic.oup.com
A system of nonlinear stochastic equations excited by a Gaussian random term leading to a
statistically stationary solution is considered. The Carleman linearization is used to handle …