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OPTIMAL CONTROL FOR STOCHASTIC VOLTERRA EQUATIONSWITH COMPLETELY MONOTONE KERNELS

机译:带有完整单调内核的随机Volterra方程的最优控制

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In this paper, we study a class of optimal control problems for stochastic Volterra equations in infinite dimensions. We are concerned with a class of stochastic Volterra integro-differential problem with completely monotone kernels, where we assume that the noise enters the system when we introducea control. We provide a semigroup setting for the problem, by the state space setting; the applications to optimal control provide other interesting results and require a precise description of the properties of the generated semigroup. In our stochastic optimal control problems, the drift term of the equation has a linear growth in the control variable, the cost functional has a quadratic growth. and the control process belongs to the class of square integrable, adapted processes with no bound assumed on it. Our main results are the existence for the optimal feedback control, the identification of the optimal cost with the value Y_0 of the maximal solution (Y, Z) of the backward stochastic differential equation, the existence of a weak solution to the so-called closed loop equation and. finally, the construction of an optimal feedback in terms of the process Z.
机译:在本文中,我们研究了无限维随机Volterra方程的一类最优控制问题。我们关注一类具有完全单调核的随机Volterra积分微分问题,其中我们在引入控制时假设噪声进入系统。我们通过状态空间设置为问题提供半组设置;最佳控制的应用程序还提供了其他有趣的结果,并且需要精确描述生成的半群的性质。在我们的随机最优控制问题中,方程的漂移项在控制变量中具有线性增长,成本函数具有二次增长。并且控制过程属于正方形可积的,自适应的过程,上面没有任何假定。我们的主要结果是最优反馈控制的存在,使用后向随机微分方程的最大解(Y,Z)的值Y_0识别最优成本,存在所谓的闭合解的弱解循环方程式和。最后,根据过程Z构造最佳反馈。

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