On the relationship between stochastic turnpike and dissipativity notions

Fuente: arXiv
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Auteurs principaux: Schießl, Jonas, Baumann, Michael H., Faulwasser, Timm, Grüne, Lars
Format: Preprint
Publié: 2023
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author Schießl, Jonas
Baumann, Michael H.
Faulwasser, Timm
Grüne, Lars
author_facet Schießl, Jonas
Baumann, Michael H.
Faulwasser, Timm
Grüne, Lars
contents In this paper, we introduce and study different dissipativity notions and different turnpike properties for discrete-time stochastic nonlinear optimal control problems. The proposed stochastic dissipativity notions extend the classic notion of Jan C. Willems to $L^r$ random variables and to probability measures. Our stochastic turnpike properties range from a formulation for random variables via turnpike phenomena in probability and in probability measures to the turnpike property for the moments. Moreover, we investigate how different metrics (such as Wasserstein or Lévy-Prokhorov) can be leveraged in the analysis. Our results are built upon stationarity concepts in distribution and in random variables and on the formulation of the stochastic optimal control problem as a finite-horizon Markov decision process. We investigate how the proposed dissipativity notions connect to the various stochastic turnpike properties and we work out the link between different forms of dissipativity.
format Preprint
id arxiv_https___arxiv_org_abs_2311_07281
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle On the relationship between stochastic turnpike and dissipativity notions
Schießl, Jonas
Baumann, Michael H.
Faulwasser, Timm
Grüne, Lars
Optimization and Control
In this paper, we introduce and study different dissipativity notions and different turnpike properties for discrete-time stochastic nonlinear optimal control problems. The proposed stochastic dissipativity notions extend the classic notion of Jan C. Willems to $L^r$ random variables and to probability measures. Our stochastic turnpike properties range from a formulation for random variables via turnpike phenomena in probability and in probability measures to the turnpike property for the moments. Moreover, we investigate how different metrics (such as Wasserstein or Lévy-Prokhorov) can be leveraged in the analysis. Our results are built upon stationarity concepts in distribution and in random variables and on the formulation of the stochastic optimal control problem as a finite-horizon Markov decision process. We investigate how the proposed dissipativity notions connect to the various stochastic turnpike properties and we work out the link between different forms of dissipativity.
title On the relationship between stochastic turnpike and dissipativity notions
topic Optimization and Control
url https://arxiv.org/abs/2311.07281