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Singular optimal controls for stochastic recursive systems under convex control constraint

机译:凸控制约束下随机递归系统的奇异最优控制

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In this paper, we study two kinds of singular optimal controls (SOCs for short) problems where the systems governed by forward-backward stochastic differential equations (FBSDEs for short), in which the control has two components: the regular control, and the singular one. Both drift and diffusion terms may involve the regular control variable. The regular control domain is postulated to be convex. Under certain assumptions, in the framework of the Malliavin calculus, we derive the pointwise second-order necessary conditions for stochastic SOC in the classical sense. This condition is described by two adjoint processes, a maximum condition on the Hamiltonian supported by an illustrative example. A new necessary condition for optimal singular control is obtained as well. Besides, as a by-product, a verification theorem for SOCs is derived via viscosity solutions without involving any derivatives of the value functions. It is worth pointing out that this theorem has wider applicability than the restrictive classical verification theorems. Finally, we focus on the connection between the maximum principle and the dynamic programming principle for such SOCs problem without the assumption that the value function is smooth enough. (C) 2020 Elsevier Inc. All rights reserved.
机译:本文研究了两类奇异最优控制问题,其中系统由正倒向随机微分方程(FBSDE)控制,其中控制有两个部分:正则控制和奇异控制。漂移项和扩散项都可能涉及规则控制变量。假设正则控制域是凸的。在一定的假设下,在Malliavin演算的框架下,我们推导了经典意义下随机SOC的点态二阶必要条件。这个条件由两个伴随过程描述,一个例子支持哈密顿量的最大条件。得到了最优奇异控制的一个新的必要条件。此外,作为副产品,通过粘度解推导出了SOCs的验证定理,而不涉及值函数的任何导数。值得指出的是,该定理比限制性经典验证定理具有更广泛的适用性。最后,在不假设值函数足够光滑的情况下,我们重点讨论了这类SOCs问题的最大值原理和动态规划原理之间的联系。(C) 2020爱思唯尔公司版权所有。

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