The Information Structure of Feedforward/Preview Control Using Forecast Data
The Information Structure of Feedforward/Preview Control Using Forecast Data
复制标题
使用预测数据的前馈/预览控制的信息结构
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
B. Sleegers
中科院分区：
文献类型：
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作者：
Robert H. Moroto;R. Bitmead;B. Sleegers
摘要在离散时间线性二次型高斯（LQG）控制的背景下，研究了扰动信号的前馈不完全预测测量的预见控制。一种新的方法，将这种预测测量直接建立在已建立的预览控制模型和结果。最优控制增益的计算，其中一个有效的计算已经被推导出来，被发现是独立的随机预测测量，这意味着最优状态估计是在这个问题的设置发生的性能改善。最重要的是，所示的预测数据模型装备的问题与嵌套的信息结构，从而任何预测前馈控制问题的一个固定的地平线长度总是相当于一个问题，一个较长的地平线和无限不可靠的预测测量超出较小的地平线长度。数值算例说明了预测时域长度和数据质量对闭环系统性能的影响。
Abstract Preview control using a fedforward imperfect forecast measurement of a disturbance signal is investigated in the context of discrete-time linear quadratic Gaussian (LQG) control. A new approach for incorporating such forecast measurements is built directly on established preview control models and results. The calculation of the optimal control gain, for which an efficient computation has already been derived, is found to be independent of the stochastic forecast measurements, implying that the optimal state estimator is where performance improvements in this problem set-up occur. Most significantly, the forecast data model is shown to equip the problem with a nested information structure whereby any forecast feedforward control problem of a fixed horizon length is always equivalent to a problem with a longer horizon and infinitely unreliable forecast measurements beyond the smaller horizon length. A numerical example illustrates the effect of forecast horizon length and data quality on the closed-loop system performance.