SIAM Journal on Control and Optimization, Volume 58, Issue 3, Page 1341-1370, January 2020.
In this paper, we consider a stochastic recursive optimal control problem under model uncertainty. In this framework, the cost function is described by solutions of a family of backward stochastic differential equations with uncertainty parameter $\theta$, which is used to represent different market conditions. With the help of linearization techniques and weak convergence methods, we derive the corresponding stochastic maximum principle. Moreover, a linear quadratic robust control problem is also studied.

中文翻译：

---

模型不确定性下随机递归最优控制问题的最大原理

SIAM控制与优化杂志，第58卷，第3期，第1341-1370页，2020
年1月。在本文中，我们考虑模型不确定性下的随机递归最优控制问题。在此框架中，成本函数由不确定性参数为\\ theta的一族倒向随机微分方程的解描述，用于表示不同的市场条件。借助于线性化技术和弱收敛方法，我们推导了相应的随机最大值原理。此外，还研究了线性二次鲁棒控制问题。