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Estimates on the Minimal Stabilizing Horizon Length in Model Predictive Control for the Fokker-Planck Equation

机译:Fokker-Planck方程的模型预测控制中的最小稳定视域长度的估计

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In a series of papers by Annunziato and Borzì, Model Predictive Control of the Fokker-Planck equation has been established as a numerically feasible way for controlling stochastic processes via their probability density functions. Numerical simulations suggest that the resulting controller yields an asymptotically stable closed loop system for optimization horizons looking only one time step into the future. In this paper we provide a formal proof of this fact for the Fokker-Planck equation corresponding to the controlled Ornstein-Uhlenbeck process using an L 2 cost and control functions that are constant in space. The key step of the proof consists in the verification of an exponential controllability property with respect to the stage cost. Numerical simulations are provided to illustrate our results.
机译:在Annunziato和Borzì的一系列论文中,已经建立了Fokker-Planck方程的模型预测控制作为通过概率密度函数控制随机过程的数值可行方法。数值模拟表明,最终的控制器会产生一个渐近稳定的闭环系统,用于优化视野,仅需一步步即可实现。在本文中,我们为Fokker-Planck方程提供了这一事实的形式证明,该方程与使用L 2成本和空间恒定的控制函数的受控Ornstein-Uhlenbeck过程相对应。证明的关键步骤在于验证与阶段成本相关的指数可控性。提供数值模拟来说明我们的结果。

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