Uniform-in-time bounds for a stochastic hybrid system with fast periodic sampling and small white-noise

We study the asymptotic behavior, uniform-in-time, of a nonlinear dynamical system under the combined effects of fast periodic sampling with period [Formula: see text] and small white noise of size [Formula: see text]. The dynamics depend on both the current and recent measurements of the state, and as such it is not Markovian. Our main results can be interpreted as Law of Large Numbers (LLN) and Central Limit Theorem (CLT) type results. LLN type result shows that the resulting stochastic process is close to an ordinary differential equation (ODE) uniformly in time as [Formula: see text] Further, in regards to CLT, we provide quantitative and uniform-in-time control of the fluctuations process. The interaction of the small parameters provides an additional drift term in the limiting fluctuations, which captures both the sampling and noise effects. As a consequence, we obtain a first-order perturbation expansion of the stochastic process along with time-independent estimates on the remainder. The zeroth- and first-order terms in the expansion are given by an ODE and SDE, respectively. Simulation studies that illustrate and supplement the theoretical results are also provided.

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Publication Details

Journal
Stochastics and Dynamics
Published
2025-02-01
DOI
https://doi.org/10.1142/s0219493725500066
Primary Topic
Control Systems and Identification
Type
article
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article

Uniform-in-time bounds for a stochastic hybrid system with fast periodic sampling and small white-noise

Konstantinos V. Spiliopoulos, Shivam Dhama
Stochastics and Dynamics
Control Systems and Identification
article

Uniform-in-time bounds for a stochastic hybrid system with fast periodic sampling and small white-noise

Konstantinos V. Spiliopoulos, Shivam Dhama
article en

Abstract

We study the asymptotic behavior, uniform-in-time, of a nonlinear dynamical system under the combined effects of fast periodic sampling with period [Formula: see text] and small white noise of size [Formula: see text]. The dynamics depend on both the current and recent measurements of the state, and as such it is not Markovian. Our main results can be interpreted as Law of Large Numbers (LLN) and Central Limit Theorem (CLT) type results. LLN type result shows that the resulting stochastic process is close to an ordinary differential equation (ODE) uniformly in time as [Formula: see text] Further, in regards to CLT, we provide quantitative and uniform-in-time control of the fluctuations process. The interaction of the small parameters provides an additional drift term in the limiting fluctuations, which captures both the sampling and noise effects. As a consequence, we obtain a first-order perturbation expansion of the stochastic process along with time-independent estimates on the remainder. The zeroth- and first-order terms in the expansion are given by an ODE and SDE, respectively. Simulation studies that illustrate and supplement the theoretical results are also provided.

Stochastics and DynamicsVol. 25(01)
Boston University (US)
Openalex Percentile: Top 98%
Control Systems and Identification
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