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Hamilton-Jacobi-Bellman Equation for a Time-Optimal Control Problem in the Space of Probability Measures

机译:概率测度空间中时间最优控制问题的Hamilton-Jacobi-Bellman方程

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In this paper we formulate a time-optimal control problem in the space of probability measures endowed with the Wasserstein metric as a natural generalization of the correspondent classical problem in R$d where the controlled dynamics is given by a differential inclusion. The main motivation is to model situations in which we have only a probabilistic knowledge of the initial state. In particular we prove first a Dynamic Programming Principle and then we give an Hamilton-Jacobi-Bellman equation in the space of probability measures which is solved by a generalization of the minimum time function in a suitable viscosity sense.
机译:在本文中,我们在Wasserstein度量所赋予的概率测度空间中,将时间最优控制问题公式化为R $ d中对应经典问题的自然概括,其中受控动力学由微分包含给出。主要动机是对我们仅有初始状态的概率知识的情况进行建模。特别是,我们首先证明了动态规划原理,然后在概率测度的空间内给出了Hamilton-Jacobi-Bellman方程,该方程通过在适当的粘度意义上最小时间函数的泛化来求解。

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