基于统计学习理论的稳健预测控制

Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206) Pub Date : 2001-09-05 DOI:10.1109/ISIC.2001.971485

J. Stecha, Z. Vlcek

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引用次数: 0

摘要

本文采用蒙特卡罗方法来解决不确定系统的预测控制问题。蒙特卡罗方法使用未知变量的样本。该方法能够解决所选准则的最小化问题和均值计算问题。对于非线性不确定系统，目前还没有求解最优控制问题的一般解析方法，该方法给出了具有规定精度的解。

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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Robust predictive control by statistical learning theory

Monte Carlo approach is used in this paper to solve predictive control problem of an uncertain system. Monte Carlo approach uses samples of unknown variables. This approach enables to solve the minimization problem and the mean value computation of the chosen criterion. For nonlinear uncertain systems there is no general analytical method how to solve the optimal control problem and our approach gives solution with prescribed accuracy.

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Proceeding of the 2001 IEEE International Symposium on Intelligent Control (ISIC '01) (Cat. No.01CH37206)

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