On state‐constrained porous‐media systems with gradient‐type multiplicative noise

Author:

Ciotir Ioana12,Goreac Dan34,Munteanu Ionut́56ORCID

Affiliation:

1. INSA de Rouen Normandie Normandie University LMI 76000 Rouen France

2. Research Center for Pure and App. Math., Graduate School of Information Sciences Tohoku University Japan

3. School of Mathematics and Statistics Shandong University, Weihai Weihai 264209 China

4. LAMA, Univ Gustave Eiffel, UPEM Univ Paris Est Creteil CNRS F‐77447 Marne‐la‐Vallée France

5. Faculty of Mathematics Al. I. Cuza University Bd. Carol I, 11 Iasi 700506 Romania

6. O. Mayer Institute of Mathematics Romanian Academy Bd. Carol I, 8 Iasi 700505 Romania

Abstract

AbstractThe aim of the present paper is to provide necessary and sufficient conditions to maintain a stochastic coupled system with porous media components and gradient‐type noise in a prescribed set of constraints by using internal controls. This work is a complementary contribution to the results obtained by the same authors, also on the viability problem associated to the porous media equation, but with Lipschitz noise. Second, the present paper provides a different framework in which the quasi‐tangency condition can be obtained with optimal speed. In comparison with the aforementioned result, and from a technical point of view, here, we transform the stochastic system into a random‐PDE one, via the rescaling approach, and then we study the viability of random sets. As an application, (stronger) conditions for the stabilization of the stochastic porous media equations are obtained. These are illustrated on a simple example.

Funder

Higher Education Discipline Innovation Project

Agence Nationale de la Recherche

National Key Research and Development Program of China

Publisher

Wiley

Subject

Control and Systems Engineering,Electrical and Electronic Engineering,Mathematics (miscellaneous)

Reference23 articles.

1. Stochastic Porous Media Equations

2. Existence and convergence results for infinite dimensional nonlinear stochastic equations with multiplicative noise

3. Strong convergence rates in averaging principle for slow-fast McKean-Vlasov SPDEs

4. I.Ciotir D.Goreac andI.Munteanu 2022. arXiv:2201.08713.

5. Uber die lage derintegralkurven gewhnlicher differentialgleichungen;Nagumo M.;Proc. Phys. Math. Soc. Japan,1942

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