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HJB and Fokker-Planck equations for river environmental management based on stochastic impulse control with discrete and random observation

机译:基于随机脉冲控制的离散和随机观察,HJB和Fokker-Planck方程

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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.
机译:基于跳跃随机微分方程(SDES)制定新的双变河环境恢复问题,治疗大坝下游河流沉积物储存和滋扰底栖藻类种群动态的沉积物储存和滋扰。通过脉冲沉积物补充来控制动态,具有离散和随机观察/干预,以避免沉积物耗竭和厚藻类生长。我们考虑了SDE的经济有效的管理问题,以实现其分辨率减少到求解Hamilton-jacobi-Bellman(HJB)方程的目标。我们还考虑一个有关控制动态的概率密度函数的Fokker-Planck(FP)方程。 HJB方程具有不连续的解决方案,而FP方程沿着沿着界限具有DIDAC的三角洲。我们表明,值函数(优化的目标函数)由简化案例中的HJB方程管理,并且进一步阈值型控制是最佳的。我们证明了简单的数字方案可以处理这些方程。最后,我们在数值上分析了最佳控制和所产生的概率密度函数。

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