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Most of the existing characterizations of the integral input-to-state stability (iISS) property are not valid for time-varying or switched systems in cases where converse Lyapunov theorems for stability are not available. This note provides…

Systems and Control · Computer Science 2017-02-02 H. Haimovich , J. L. Mancilla-Aguilar

Khasminski's \cite{chas1980stochastic} showed that many of the asymptotic stability and the integrability properties of the solutions to the Stochastic Differential Equations (SDEs) can be obtained using Lyapunov functions techniques. These…

Numerical Analysis · Mathematics 2016-08-11 Lukasz Szpruch , X\=ılíng Zhāng

This paper presents new sufficient conditions for convergence and asymptotic or exponential stability of a stochastic discrete-time system, under which the constructed Lyapunov function always decreases in expectation along the system's…

Systems and Control · Computer Science 2019-06-05 Yuzhen Qin , Ming Cao , Brian D. O. Anderson

We study the positive recurrence of multi-dimensional birth-and-death processes describing the evolution of a large class of stochastic systems, a typical example being the randomly varying number of flow-level transfers in a…

Probability · Mathematics 2009-11-02 M. Jonckheere , S. Shneer

Stochastic uncertainties in complex dynamical systems lead to variability of system states, which can in turn degrade the closed-loop performance. This paper presents a stochastic model predictive control approach for a class of nonlinear…

Optimization and Control · Mathematics 2016-11-18 Edward A. Buehler , Joel A. Paulson , Ali Akhavan , Ali Mesbah

In this paper, we develop tools to establish almost sure stability of stochastic switched systems whose switching signal is constrained by an automaton. After having provided the necessary generalizations of existing results in the setting…

Optimization and Control · Mathematics 2022-08-26 Matteo Della Rossa , Raphaël M. Jungers

In this work we introduce a theory of stochastic integration with respect to general cylindrical semimartingales defined on a locally convex space $\Phi$. Our construction of the stochastic integral is based on the theory of tensor products…

Probability · Mathematics 2021-12-06 C. A. Fonseca-Mora

This paper presents a continuous and discrete Lagrangian theory for stochastic Hamiltonian systems on manifolds. The main result is to derive stochastic governing equations for such systems from a critical point of a stochastic action.…

Probability · Mathematics 2009-06-02 Nawaf Bou-Rabee , Houman Owhadi

This paper studies stochastic boundedness of trajectories of a nonvanishing stochastically perturbed stable LTI system. First, two definitions on stochastic boundedness of stochastic processes are presented, then the boundedness is analyzed…

Optimization and Control · Mathematics 2017-04-18 Peyman Azodi , Alireza Khayatian , Elham Jamalinia , Peyman Setoodeh

The main purpose of this work is to characterize the almost sure local structure stability of solutions to a class of linear stochastic partial functional differential equations (SPFDEs) by investigating the Lyapunov exponents and invariant…

Dynamical Systems · Mathematics 2023-10-20 Wenjie Hu , Tomás Caraballo

This paper deals with input/output-to-state stability (IOSS) of continuous-time switched nonlinear systems. Given a family of systems, possibly containing unstable dynamics, and a set of restrictions on admissible switches between the…

Optimization and Control · Mathematics 2023-06-21 Atreyee Kundu

We consider parabolic PDEs with randomly switching boundary conditions. In order to analyze these random PDEs, we consider more general stochastic hybrid systems and prove convergence to, and properties of, a stationary distribution.…

Probability · Mathematics 2020-03-13 Sean D. Lawley , Jonathan C. Mattingly , Michael C. Reed

Stability, reachability, and safety are crucial properties of dynamical systems. While verification and control synthesis of reach-avoid-stay objectives can be effectively handled by abstraction-based formal methods, such approaches can be…

Dynamical Systems · Mathematics 2022-11-03 Yiming Meng , Jun Liu

Stochastic differential equations of Langevin-diffusion form have received significant attention, thanks to their foundational role in both Bayesian sampling algorithms and optimization in machine learning. In the latter, they serve as a…

Optimization and Control · Mathematics 2024-05-14 Fabio V. Difonzo , Vyacheslav Kungurtsev , Jakub Marecek

This article is concerned with stability analysis and stabilization of randomly switched nonlinear systems. These systems may be regarded as piecewise deterministic stochastic systems: the discrete switches are triggered by a stochastic…

Optimization and Control · Mathematics 2010-09-08 Debasish Chatterjee , Daniel Liberzon

We propose a framework to analyze stability for a class of linear non-autonomous hybrid systems, where the continuous evolution of solutions is governed by an ordinary differential equation and the instantaneous changes are governed by a…

Optimization and Control · Mathematics 2023-01-24 Adnane Saoud , Mohamed Maghenem , Antonio Loría , Ricardo G. Sanfelice

The topic of this manuscript is the stability analysis of continuous-time switched nonlinear systems with constraints on the admissible switching signals. Our particular focus lies in considering signals characterized by upper and lower…

Optimization and Control · Mathematics 2024-01-17 Matteo Della Rossa

We prove that (local) input-to-state stability ((L)ISS) and integral input-to-state stability (iISS) of time-varying infinite-dimensional systems in abstract spaces follows from the existence of a {corresponding} Lyapunov function. In…

Optimization and Control · Mathematics 2025-10-17 Rahma Heni , Andrii Mironchenko , Fabian Wirth , Hanen Damak , Mohamed Ali Hammami

In this paper we revisit a fundamental technical issue within the theory of stochastic approximation (SA) in a Markovian framework, first proposed in the book by Djereveckii and Fradkov (1981), and further developed in much detail in the…

We are interested in understanding stability (almost sure boundedness) of stochastic approximation algorithms (SAs) driven by a `controlled Markov' process. Analyzing this class of algorithms is important, since many reinforcement learning…

Systems and Control · Computer Science 2018-05-18 Arunselvan Ramaswamy , Shalabh Bhatnagar