A Gradient Method for Risk Averse Control of a PDE-SDE Interconnected System

Fuente: arXiv
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Main Authors: Velho, Gabriel, Auriol, Jean, Bonalli, Riccardo
Format: Preprint
Published: 2025
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author Velho, Gabriel
Auriol, Jean
Bonalli, Riccardo
author_facet Velho, Gabriel
Auriol, Jean
Bonalli, Riccardo
contents In this paper, we design a risk-averse controller for an interconnected system composed of a linear Stochastic Differential Equation (SDE) actuated through a linear parabolic heat equation. These dynamics arise in various applications, such as coupled heat transfer systems and chemical reaction processes that are subject to disturbances. While existing optimal control methods for these systems focus on minimizing average performance, this risk-neutral perspective may allow rare but highly undesirable system behaviors. To account for such events, we instead minimize the cost within a coherent risk measure. Our approach reformulates the coupled dynamics as a stochastic PDE, approximates it by a finite-dimensional SDE system, and applies a gradient-based method to compute a riskaverse feedback controller. Numerical simulations show that the proposed controller substantially reduces the tail of the cost distribution, improving reliability with only a minor reduction in average performance.
format Preprint
id arxiv_https___arxiv_org_abs_2512_03626
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle A Gradient Method for Risk Averse Control of a PDE-SDE Interconnected System
Velho, Gabriel
Auriol, Jean
Bonalli, Riccardo
Optimization and Control
In this paper, we design a risk-averse controller for an interconnected system composed of a linear Stochastic Differential Equation (SDE) actuated through a linear parabolic heat equation. These dynamics arise in various applications, such as coupled heat transfer systems and chemical reaction processes that are subject to disturbances. While existing optimal control methods for these systems focus on minimizing average performance, this risk-neutral perspective may allow rare but highly undesirable system behaviors. To account for such events, we instead minimize the cost within a coherent risk measure. Our approach reformulates the coupled dynamics as a stochastic PDE, approximates it by a finite-dimensional SDE system, and applies a gradient-based method to compute a riskaverse feedback controller. Numerical simulations show that the proposed controller substantially reduces the tail of the cost distribution, improving reliability with only a minor reduction in average performance.
title A Gradient Method for Risk Averse Control of a PDE-SDE Interconnected System
topic Optimization and Control
url https://arxiv.org/abs/2512.03626