Research article

Stochastic differential equations in infinite dimensional Hilbert space and its optimal control problem with Lévy processes

  • Received: 12 April 2021 Accepted: 04 November 2021 Published: 12 November 2021
  • MSC : 60H10, 93E24

  • The paper is concerned with a class of stochastic differential equations in infinite dimensional Hilbert space with random coefficients driven by Teugels martingales which are more general processes and the corresponding optimal control problems. Here Teugels martingales are a family of pairwise strongly orthonormal martingales associated with Lévy processes (see Nualart and Schoutens [21]). There are three major ingredients. The first is to prove the existence and uniqueness of the solutions by continuous dependence theorem of solutions combining with the parameter extension method. The second is to establish the stochastic maximum principle and verification theorem for our optimal control problem by the classic convex variation method and dual techniques. The third is to represent an example of a Cauchy problem for a controlled stochastic partial differential equation driven by Teugels martingales which our theoretical results can solve.

    Citation: Meijiao Wang, Qiuhong Shi, Maoning Tang, Qingxin Meng. Stochastic differential equations in infinite dimensional Hilbert space and its optimal control problem with Lévy processes[J]. AIMS Mathematics, 2022, 7(2): 2427-2455. doi: 10.3934/math.2022137

    Related Papers:

  • The paper is concerned with a class of stochastic differential equations in infinite dimensional Hilbert space with random coefficients driven by Teugels martingales which are more general processes and the corresponding optimal control problems. Here Teugels martingales are a family of pairwise strongly orthonormal martingales associated with Lévy processes (see Nualart and Schoutens [21]). There are three major ingredients. The first is to prove the existence and uniqueness of the solutions by continuous dependence theorem of solutions combining with the parameter extension method. The second is to establish the stochastic maximum principle and verification theorem for our optimal control problem by the classic convex variation method and dual techniques. The third is to represent an example of a Cauchy problem for a controlled stochastic partial differential equation driven by Teugels martingales which our theoretical results can solve.



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