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A stochastic maximum principle for delayed mean-field stochastic differential equations and its applications

机译:时滞平均场随机微分方程的最大随机原理及其应用

摘要

In this technical note, we discuss the stochastic optimal control problems of mean-field stochastic differential delayed equations (MFSDDEs) which arise naturally from various backgrounds including economics, finance, engineering and physics, etc. To this end, some new estimates are used to handle the complex structure of our controlled system due to the presence of both delay and mean-field characters. As the main result, a stochastic maximum principle for the mean-field stochastic optimal control with delay (MFSOCD) is derived in terms of necessary and sufficient conditions. In particular, applying the convex variation and duality relation, we obtain the necessary condition for optimality (see Theorem 1). In addition, the sufficient condition of the optimality is also obtained under some convex condition (see Theorem 2). Based on our maximum principle, the related mean-field linear quadratic delayed (MFLQD) optimal control problems are also investigated. The optimal control is derived and its existence is also verified (refer Theorem 3). As illustration, an example is also proposed and its explicit optimal control is derived.
机译:在本技术说明中,我们讨论了均场随机微分延迟方程(MFSDDE)的随机最优控制问题,该方程自然源于各种背景,包括经济学,金融学,工程学和物理学等。为此,一些新的估计用于由于存在延迟和均场特性,因此可以处理我们受控系统的复杂结构。作为主要结果,根据必要条件和充分条件,推导了具有时滞的平均场随机最优控制(MFSOCD)的随机最大原理。特别地,应用凸变率和对偶关系,我们获得了最优性的必要条件(见定理1)。另外,在某些凸条件下也可以获得最优性的充分条件(见定理2)。基于我们的最大原理,还研究了相关的平均场线性二次延迟(MFLQD)最优控制问题。推导了最优控制,并验证了其存在性(请参见定理3)。作为说明,还提出了一个示例,并推导了其显式最优控制。

著录项

  • 作者

    Du H; Huang J; Qin Y;

  • 作者单位
  • 年度 2013
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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