Feedback control for stochastic gas flow

TL;DR

This paper extends deterministic feedback control methods to stabilize stochastic gas flow described by hyperbolic balance laws with Gaussian process influences, addressing computational challenges for complex random fields.

Contribution

It introduces a stabilization approach for stochastic gas flow models influenced by Gaussian processes, expanding deterministic control techniques to stochastic settings.

Findings

Stability with exponential decay of deviations at steady state.

Extension of control methods to Gaussian stochastic influences.

Discussion of computational complexity issues.

Abstract

We consider linear hyperbolic balance law that describe gas flow. Stochastic influences are introduced by series of orthogonal functions. A deterministic stabilization concept, which makes deviations at steady states decay exponentially fast, is extended to stochastic influences. These can be described by general Gaussian processes. The computational complexity, however, may prevent an application to certain random fields.