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arXiv 1504.04889math.PRmath.DSmath.OC
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随机扰动动力学中的受控平衡选择

Controlled equilibrium selection in stochastically perturbed dynamics

Ari Arapostathis, Anup Biswas, Vivek S. Borkar

摘要:

我们考虑一个动力系统,除了被一个“昂贵的”控制,还具有许多平衡点和小噪声扰动。被控过程是最优的遍历标准的运行成本,包括控制努力和状态空间上的罚函数的总和。我们研究的最佳平稳分布的受控过程的方差的噪声变得非常小。它示出,根据噪声方差和“运行成本”的控制的相对大小,可以确定三个制度,在每一个其中的最优控制的力量的不变分布的过程中,可以根据政权的特点,集中在平衡附近。我们还获得了最佳平稳分布的矩界。此外,我们表明,在附近的点的浓度的最佳平稳分布的密度近似的高斯密度,我们明确解决其协方差阵。

英文摘要:

We consider a dynamical system with finitely many equilibria and perturbed by small noise, in addition to being controlled by an `expensive' control. The controlled process is optimal for an ergodic criterion with a running cost that consists the sum of the control effort and a penalty function on the state space. We study the optimal stationary distribution of the controlled process as the variance of the noise becomes vanishingly small. It is shown that depending on the relative magnitudes of the noise variance and the `running cost' for control, one can identify three regimes, in each of which the optimal control forces the invariant distribution of the process to concentrate near equilibria that can be characterized according to the regime. We also obtain moment bounds for the optimal stationary distribution. Moreover, we show that in the vicinity of the points of concentration the density of optimal stationary distribution approximates the density of a Gaussian, and we explicitly solve for its covariance matrix.

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