无限维带跳倒向随机线性二次最优控制问题
Infinite-Dimensional Backward Stochastic Linear-Quadratic Optimal Control Problem with Jumps
-
摘要: 本文研究一类无限维Hilbert空间中由布朗运动和补偿泊松随机测度共同驱动的带跳倒向随机微分方程的随机线性二次最优控制问题.首先给出无限维倒向随机微分方程强解与温和解的定义, 并利用Yosida逼近处理无界生成元导致的伊藤公式适用性问题.其次, 基于凸变分原理证明最优控制的存在性和唯一性.在此基础上, 通过构造状态方程的对偶方程推导平稳性条件, 并建立无限维随机Hamilton系统.最后, 在算子Riccati方程可解且相关算子可逆的条件下, 得到最优控制的反馈表示.Abstract: This paper studies a linear-quadratic optimal control problem for backward stochastic differential equations with jumps in an infinite-dimensional Hilbert space, driven by a Brownian motion and a compensated Poisson random measure. We first formulate strong and mild solutions and introduce the Yosida approximation to justify the use of the Itô formula in the presence of an unbounded generator. We then establish existence and uniqueness of the optimal control by a convex variational argument. By constructing the adjoint equation, we derive the stationarity condition and the associated infinite-dimensional stochastic Hamiltonian system. Finally, under solvability and invertibility assumptions for the operator Riccati equation, we obtain a feedback representation of the optimal control.
下载: