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In this paper we propose a data-driven distributionally robust Model Predictive Control framework for constrained stochastic systems with unbounded additive disturbances. Recursive feasibility is ensured by optimizing over an linearly…

Optimization and Control · Mathematics 2023-03-07 Christoph Mark , Steven Liu

The survival probability for a periodic non-autonomous Ornstein-Uhlenbeck process is calculated analytically using two different methods. The first uses an asymptotic approach. We treat the associated Kolmogorov Backward Equation with an…

Statistical Mechanics · Physics 2025-01-20 L. T. Giorgini , W. Moon , J. S. Wettlaufer

We propose a non-Gaussian operator-valued extension of the Barndorff-Nielsen and Shephard stochastic volatility dynamics, defined as the square-root of an operator-valued Ornstein-Uhlenbeck process with Levy noise and bounded drift. We…

Probability · Mathematics 2015-06-25 Fred Espen Benth , Barbara Ruediger , Andre Suess

In this paper we present a hierarchical multi-rate control architecture for nonlinear autonomous systems operating in partially observable environments. Control objectives are expressed using syntactically co-safe Linear Temporal Logic…

Systems and Control · Electrical Eng. & Systems 2022-07-04 Ugo Rosolia , Andrew Singletary , Aaron D. Ames

This paper proposes a target zones exchange rate model with a terminal condition of entering a currency zone. It is assumed that the exchange rate is a function of the fundamental and time. Another essential assumptions of the model is that…

Economics · Quantitative Finance 2015-06-17 Viktors Ajevskis

This paper considers a Markovian model of a limit order book where time-dependent rates are allowed. With the objective of understanding the mechanisms through which a microscopic model of an orderbook can converge to more general diffusion…

Computational Finance · Quantitative Finance 2023-02-03 Jonathan A. Chávez-Casillas

Motivated by the modeling of the temporal structure of the velocity field in a highly turbulent flow, we propose and study a linear stochastic differential equation that involves the ingredients of a Ornstein-Uhlenbeck process, supplemented…

Fluid Dynamics · Physics 2017-09-26 Laurent Chevillard

This paper investigates the optimal control problem for a class of discrete-time stochastic systems subject to additive and multiplicative noises. A stochastic Lyapunov equation and a stochastic algebra Riccati equation are established for…

Systems and Control · Electrical Eng. & Systems 2020-08-24 Jing Lai , Junlin Xiong , Zhan Shu

Traditional solvable optimal control theory predominantly focuses on quadratic costs due to their analytical tractability, yet they often fail to capture critical non-linearities inherent in real-world systems including water, energy,…

Optimization and Control · Mathematics 2025-05-22 Julian Barreiro-Gomez , Tyrone E. Duncan , Bozenna Pasik-Duncan , Hamidou Tembine

We conduct modeling of the price dynamics following order flow imbalance in market microstructure and apply the model to the analysis of Chinese CSI 300 Index Futures. There are three findings. The first is that the order flow imbalance is…

Mathematical Finance · Quantitative Finance 2025-05-26 Chen Hu , Kouxiao Zhang

We refer by threshold Ornstein-Uhlenbeck to a continuous-time threshold autoregressive process. It follows the Ornstein-Uhlenbeck dynamics when above or below a fixed level, yet at this level (threshold) its coefficients can be…

Probability · Mathematics 2022-06-07 Sara Mazzonetto , Paolo Pigato

Stochastic fluctuations of molecular abundances are a ubiquitous feature of cellular processes and lead to significant cell-to-cell variability. Recent theoretical work established lower bounds for stochastic fluctuations in cells for broad…

Molecular Networks · Quantitative Biology 2025-05-06 Brayden Kell , Andreas Hilfinger

Optimal control of interacting particles governed by stochastic evolution equations in Hilbert spaces is an open area of research. Such systems naturally arise in formulations where each particle is modeled by stochastic partial…

Probability · Mathematics 2025-11-27 Filippo de Feo , Fausto Gozzi , Andrzej Święch , Lukas Wessels

A general scheme is presented for controlling quantum systems using evolution driven by non-selective von Neumann measurements, with or without an additional tailored electromagnetic field. As an example, a 2-level quantum system controlled…

Quantum Physics · Physics 2007-05-23 Alexander Pechen , Nikolai Il'in , Feng Shuang , Herschel Rabitz

This paper studies the problem of trading futures with transaction costs when the underlying spot price is mean-reverting. Specifically, we model the spot dynamics by the Ornstein-Uhlenbeck (OU), Cox-Ingersoll-Ross (CIR), or exponential…

Mathematical Finance · Quantitative Finance 2016-01-19 Tim Leung , Jiao Li , Xin Li , Zheng Wang

A new method for stochastic control based on neural networks and using randomisation of discrete random variables is proposed and applied to optimal stopping time problems. The method models directly the policy and does not need the…

Computational Finance · Quantitative Finance 2021-01-11 Thomas Deschatre , Joseph Mikael

Cellular responses to death-promoting stimuli typically proceed through a differentiated multistage process, involving a lag phase, extensive death, and potential adaptation. Deregulation of this chain of events is at the root of many…

Cell Behavior · Quantitative Biology 2010-12-03 Jose M. G. Vilar

Change of measures has been an effective method in stochastic control and analysis; in continuous-time control this follows Girsanov's theorem applied to both fully observed and partially observed models, in decentralized stochastic control…

Optimization and Control · Mathematics 2022-01-20 Ian Hogeboom-Burr , Serdar Yüksel

In this paper, we study the regularity of the value function associated with a stochastic control problem where two controls act simultaneously on a modulated multidimensional diffusion process. The first is a switching control modelling a…

Optimization and Control · Mathematics 2022-12-02 Mark Kelbert , Harold A. Moreno-Franco

In Stochastic Optimal Control (SOC) one minimizes the average cost-to-go, that consists of the cost-of-control (amount of efforts), cost-of-space (where one wants the system to be) and the target cost (where one wants the system to arrive),…

Statistical Mechanics · Physics 2020-09-29 Vladimir Y. Chernyak , Michael Chertkov , Joris Bierkens , Hilbert J. Kappen
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