Incremental Input-to-State Stability and Equilibrium Tracking for Stochastic Contracting Dynamics

Fuente: arXiv
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Autores principales: Kawano, Yu, Betteti, Simone, Davydov, Alexander, Bullo, Francesco
Formato: Preprint
Publicado: 2026
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author Kawano, Yu
Betteti, Simone
Davydov, Alexander
Bullo, Francesco
author_facet Kawano, Yu
Betteti, Simone
Davydov, Alexander
Bullo, Francesco
contents In this paper, we study the contractivity of nonlinear stochastic differential equations (SDEs) driven by deterministic inputs and Brownian motions. Given a weighted $\ell_2$-norm for the state space, we show that an SDE is incrementally noise- and input-to-state stable if its vector field is uniformly contracting in the state and uniformly Lipschitz in the input. This result is applied to error estimation for time-varying equilibrium tracking in the presence of noise affecting both the system dynamics and the input signals. We consider both Ornstein-Uhlenbeck processes modeling unbounded noise and Jacobi diffusion processes modeling bounded noise. Finally, we turn our attention to the associated Fokker-Planck equation of an SDE. For this context, we prove incremental input-to-state stability with respect to an arbitrary $p$-Wasserstein metric when the drift vector field is uniformly contracting in the state and uniformly Lipschitz in the input with respect to an arbitrary norm.
format Preprint
id arxiv_https___arxiv_org_abs_2602_18382
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Incremental Input-to-State Stability and Equilibrium Tracking for Stochastic Contracting Dynamics
Kawano, Yu
Betteti, Simone
Davydov, Alexander
Bullo, Francesco
Systems and Control
Optimization and Control
In this paper, we study the contractivity of nonlinear stochastic differential equations (SDEs) driven by deterministic inputs and Brownian motions. Given a weighted $\ell_2$-norm for the state space, we show that an SDE is incrementally noise- and input-to-state stable if its vector field is uniformly contracting in the state and uniformly Lipschitz in the input. This result is applied to error estimation for time-varying equilibrium tracking in the presence of noise affecting both the system dynamics and the input signals. We consider both Ornstein-Uhlenbeck processes modeling unbounded noise and Jacobi diffusion processes modeling bounded noise. Finally, we turn our attention to the associated Fokker-Planck equation of an SDE. For this context, we prove incremental input-to-state stability with respect to an arbitrary $p$-Wasserstein metric when the drift vector field is uniformly contracting in the state and uniformly Lipschitz in the input with respect to an arbitrary norm.
title Incremental Input-to-State Stability and Equilibrium Tracking for Stochastic Contracting Dynamics
topic Systems and Control
Optimization and Control
url https://arxiv.org/abs/2602.18382