English
Related papers

Related papers: On stochastic stabilization of sampled systems

200 papers

Second-order macroscopic continuum models have been constantly improving for decades to reproduce the empirical observations. Recently, a series of experimental studies have suggested that the stochastic factors contribute significantly to…

Physics and Society · Physics 2022-09-15 Marouane Bouadi , Bin Jia , Rui Jiang , Xingang Li , Zi-You Gao

In this paper we study the semi-global (approximate) state feedback stabilization of an infinite dimensional quantum stochastic system towards a target state. A discrete-time Markov chain on an infinite-dimensional Hilbert space is used to…

Optimization and Control · Mathematics 2011-03-22 Ram Somaraju , Mazyar Mirrahimi , Pierre Rouchon

We propose an encoding and control strategy for the stabilization of switched systems with limited information, supposing the controller is given for each mode. Only the quantized output and the active mode of the plant at each sampling…

Systems and Control · Computer Science 2014-12-19 Masashi Wakaiki , Yutaka Yamamoto

Despite the existence of formal guarantees for learning-based control approaches, the relationship between data and control performance is still poorly understood. In this paper, we propose a Lyapunov-based measure for quantifying the…

Systems and Control · Electrical Eng. & Systems 2021-08-02 Armin Lederer , Alexandre Capone , Thomas Beckers , Jonas Umlauft , Sandra Hirche

In this paper, we study the stability of solutions of stochastic McKean-Vlasov equations (SMVEs) via feedback control based on discrete-time state observation. By using a specific Lyapunov function, the $H_{\infty}$ stability, asymptotic…

Probability · Mathematics 2021-10-25 Hao Wu , Junhao Hu , Shuaibin Gao , Chenggui Yuan

This thesis develops exact analytical tools to study strongly correlated stochastic systems, with a focus on extreme value statistics, gap statistics, and full counting statistics in multi-particle processes. A central contribution is the…

Statistical Mechanics · Physics 2025-08-19 Marco Biroli

We design the controls of physical systems that are faced by uncertainties. The system dynamics are described by random hyperbolic balance laws. The control aims to steer the system to a desired state under uncertainties. We propose a…

Optimization and Control · Mathematics 2021-07-20 Stephan Gerster , Markus Bambach , Michael Herty , Muhammad Imran

Controllers for autonomous systems that operate in safety-critical settings must account for stochastic disturbances. Such disturbances are often modelled as process noise, and common assumptions are that the underlying distributions are…

Systems and Control · Electrical Eng. & Systems 2022-12-08 Thom S. Badings , Alessandro Abate , Nils Jansen , David Parker , Hasan A. Poonawala , Marielle Stoelinga

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

The paper proposes the stable motion control law design method for non-honomic differential-drive mobile robot with system and measurement noise in discrete time domain. This method is performed basing on dividing operating configuration of…

Robotics · Computer Science 2020-05-14 Thi Thanh Van Nguyen , Manh Duong Phung , Quang Vinh Tran

This survey paper deals with the stabilization of nonlinear systems by analyzing the controlling method in terms of state feedback and output feedback. A brief overview of some literature on how the feedback controller of some dynamic…

Systems and Control · Electrical Eng. & Systems 2022-01-03 Demelash Abiye Deguale

This paper tackles state feedback control of switched linear systems under arbitrary switching. We propose a data-driven control framework that allows to compute a stabilizing state feedback using only a finite set of observations of…

Optimization and Control · Mathematics 2022-05-05 Zheming Wang , Guillaume O. Berger , Raphaël M. Jungers

This paper is concerned with synchronization of complex stochastic dynamical networks in the presence of noise and functional uncertainty. A probabilistic control method for adaptive synchronization is presented. All required probabilistic…

Optimization and Control · Mathematics 2016-12-20 Randa Herzallah

Learned models and policies can generalize effectively when evaluated within the distribution of the training data, but can produce unpredictable and erroneous outputs on out-of-distribution inputs. In order to avoid distribution shift when…

Machine Learning · Computer Science 2022-06-22 Katie Kang , Paula Gradu , Jason Choi , Michael Janner , Claire Tomlin , Sergey Levine

Incremental stability is a property of dynamical systems ensuring the uniform asymptotic stability of each trajectory rather than a fixed equilibrium point or trajectory. Here, we introduce a notion of incremental stability for stochastic…

Systems and Control · Computer Science 2017-05-08 Pushpak Jagtap , Majid Zamani

This article is concerned with stability and performance of controlled stochastic processes under receding horizon policies. We carry out a systematic study of methods to guarantee stability under receding horizon policies via appropriate…

Systems and Control · Computer Science 2017-11-27 Debasish Chatterjee , John Lygeros

We prove stochastic stability of chaotic maps for a general class of Markov random perturbations (including singular ones) satisfying some kind of mixing conditions. One of the consequences of this statement is the proof of Ulam's…

chao-dyn · Physics 2017-01-16 Michael Blank , Gerhard Keller

This work deals with the stability analysis of nonlinear sampled-data systems under nonuniform sampling. It establishes novel relationships between the stability property of the exact discrete-time model for a given sequence of (aperiodic)…

Systems and Control · Electrical Eng. & Systems 2022-09-28 Alexis J. Vallarella , Hernan Haimovich

In this paper, we consider solving discounted Markov Decision Processes (MDPs) under the constraint that the resulting policy is stabilizing. In practice MDPs are solved based on some form of policy approximation. We will leverage recent…

Machine Learning · Computer Science 2021-02-03 Mario Zanon , Sébastien Gros , Michele Palladino

The stability of stochastic Model Predictive Control (MPC) subject to additive disturbances is often demonstrated in the literature by constructing Lyapunov-like inequalities that guarantee closed-loop performance bounds and boundedness of…

Optimization and Control · Mathematics 2019-03-19 Diego Munoz-Carpintero , Mark Cannon