We formulate a new two-variable river environmental restoration problem based on jump stochastic differential equations (SDEs) governing the sediment storage and nuisance benthic algae population dynamics in a dam-downstream river. Controlling the dynamics is carried out through impulsive sediment replenishment with discrete and random observation/intervention to avoid sediment depletion and thick algae growth. We consider a cost-efficient management problem of the SDEs to achieve the objectives whose resolution reduces to solving a Hamilton-Jacobi-Bellman (HJB) equation. We also consider a Fokker-Planck (FP) equation governing the probability density function of the controlled dynamics. The HJB equation has a discontinuous solution, while the FP equation has a Dirac's delta along boundaries. We show that the value function, the optimized objective function, is governed by the HJB equation in the simplified case and further that a threshold-type control is optimal. We demonstrate that simple numerical schemes can handle these equations. Finally, we numerically analyze the optimal controls and the resulting probability density functions.
翻译:我们根据关于大型下游河流沉积物储存和扰动海底藻类种群动态的跳式差异方程式(SDEs),制定了一个新的双变河环境恢复问题;通过分流和随机观测/干预的冲动沉积物补充来控制动态,以避免沉积物耗竭和藻类稠密增长;我们考虑SDEs的成本效益管理问题,以实现其分辨率降低到解决汉密尔顿-贾科比-贝尔曼(HJB)方程式的目标。我们还考虑Fokker-Planck(FP)方程式(FP)来管理控制受控动力的概率密度功能。HJB方程式有一个不连续的解决方案,而FP方方方程式沿边界有一个Dirac三角塔。我们表明,价值功能、最佳目标功能是由HJB方程式在简化的案例中管理,此外,门槛式控制是最佳的。我们证明简单的数字方案能够处理这些方程式。最后,我们用数字分析最佳控制方法和由此产生的概率密度功能。