具有更新变量遗忘因子的子空间预测控制方法

Huang Jin-feng, Zhang He-xin, Fan Jin-suo, Wu Yu-Bin
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引用次数: 0

摘要

根据带遗忘因子更新数据的一般形式,得到了更新I/O汉克尔矩阵的几个结论。在此基础上,提出了可变遗忘因子的子空间识别和相关SPC方法,提高了对时变信息的跟踪性能。遗忘因子的更新是通过期望输出与实测输出之间的距离来实现的。最后通过仿真算例说明了改进方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Subspace predictive controlle method with updating variable forgetting factor
According to the general form of updating data with forgetting factor, several conclusions are obtained in updating I/O Hankel matrices. Based on these conclusions, new subspace identification and relative SPC methods are proposed with variable forgetting factor for improving the performance in tracking the time-varying information. And the forgetting factor's update is realized by the distance between expected outputs and measured outputs. Finally, the efficiency of modified method is illustrated with a simulation example.
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