复杂随机系统的马尔可夫链蒙特卡罗预测控制及其在空中交通管制中的应用

2006 IEEE Nonlinear Statistical Signal Processing Workshop Pub Date : 2006-09-01 DOI:10.1109/NSSPW.2006.4378848

A. Lecchini, W. Glover, J. Lygeros, Jan Maciejowski

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引用次数: 3

摘要

马尔可夫链蒙特卡罗(MCMC)方法可用于在随机效应突出的非常复杂的情况下做出最优决策。本文简要介绍了MCMC在复杂随机系统预测控制中的应用以及在空中交通管制中的应用研究现状。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Predictive Control of Complex Stochastic Systems using Markov Chain Monte Carlo with Application to Air Traffic Control

Markov chain Monte Carlo (MCMC) methods can be used to make optimal decisions in very complex situations in which stochastic effects are prominent. In this paper we briefly introduce our current research on the application of MCMC to the predictive control of complex stochastic systems and the application to air traffic control.

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2006 IEEE Nonlinear Statistical Signal Processing Workshop

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