旋轉(zhuǎn)因子必須在線整定心傀，因?yàn)樗蕾囉诓豢蓽y(cè)過(guò)程干擾和測(cè)量噪聲的性質(zhì)屈暗。通常，旋轉(zhuǎn)因子在0.1到0.4之間就足夠了脂男。

圖14至17顯示了一個(gè)如何整定旋轉(zhuǎn)因子的例子养叛。在這個(gè)例子中，旋轉(zhuǎn)因子為0.2時(shí)擁有最佳控制性能宰翅。

旋轉(zhuǎn)因子過(guò)大將會(huì)導(dǎo)致預(yù)測(cè)向量在連續(xù)的控制時(shí)間間隔里從正值到負(fù)值來(lái)回波動(dòng)（見(jiàn)圖14）弃甥。這是因?yàn)轭A(yù)測(cè)向量旋轉(zhuǎn)反映的是因變量的隨機(jī)噪聲。

旋轉(zhuǎn)因子過(guò)小則會(huì)減慢預(yù)測(cè)校正的速度汁讼，并導(dǎo)致預(yù)測(cè)向量漂離希望的操作區(qū)域淆攻。如圖15所示。

一個(gè)好的預(yù)測(cè)向量旋轉(zhuǎn)因子整定如下圖16所示掉缺。

整定旋轉(zhuǎn)因子另一個(gè)有效方法是觀察預(yù)測(cè)誤差歷史記錄（見(jiàn)圖17）卜录。若旋轉(zhuǎn)因子太小，預(yù)測(cè)誤差將長(zhǎng)時(shí)間在0的一側(cè)漂移（低頻行為）眶明。旋轉(zhuǎn)因子過(guò)大將導(dǎo)致預(yù)測(cè)誤差高頻率變化。正確旋轉(zhuǎn)因子整定是一個(gè)隨機(jī)預(yù)測(cè)誤差的模式筐高。

更新頻率

注意當(dāng)一個(gè)斜坡變量是間歇變量時(shí)搜囱，變量的更新頻率將影響旋轉(zhuǎn)計(jì)算「掏粒控制器將假定預(yù)測(cè)誤差是從前面的周期蜀肘，而不是前面的更新得出的。這可能會(huì)導(dǎo)致斜率調(diào)整過(guò)于劇烈稽屏。

若更新頻率已知扮宠，則旋轉(zhuǎn)因子應(yīng)該由更新頻率（周期）劃分。若更新頻率未知或不能被近似狐榔，那么可以使用用戶計(jì)算計(jì)算在該時(shí)間所需要的旋轉(zhuǎn)因子坛增。

Figure14: Effect of a Rotation Factor that is Too Large

? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?圖14：旋轉(zhuǎn)因子影響太大

Figure15: Effect of a Rotation Factor that is Too Small

? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 圖15：旋轉(zhuǎn)因子影響太小

Figure16:Effect of Rotation Factor this is about right

? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 圖16：旋轉(zhuǎn)因子影響基本正確

Figure17:Prediction Error History for choosing Rotation Factor

? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ?圖17：通過(guò)預(yù)測(cè)誤差選擇旋轉(zhuǎn)因子

附原文：

The rotation factor must be tuned online,since it depends on the nature of the unmeasured process disturbances and the measurement noise. Generally, a rotation factor between 0.1 and 0.4 is sufficient.

Figures 14 to 17 show an example of how to tune the rotation factor. For this example, a rotation factor of 0.2gives the best control performance.

A rotation factor which is too large will cause the prediction vector to "wave" back and forth from a positive to a negative value in successive control intervals (see Figure 14).This occurs because the prediction vector rotation is reacting to random noise in the dependent variable.

A rotation factor which is too small will slow down the rate at which the prediction is corrected and cause the prediction vector to drift away from the desired operating region. See Figure 15 below.

Prediction vectors for good rotation factor tuning are shown in Figure 16.

Another useful technique for tuning rotation factors is to observe the prediction error history (see Figure17). For a rotation factor that is too small, the prediction error drifts on one side of zero for prolonged periods of time (low frequency behavior). A rotation factor that is too large will result in high frequency variation in the prediction error. The correct rotation factor tuning results in a randomized prediction error pattern.

Update frequency

Note that when a ramp is also an intermittent variable, then the variable's update frequency will impact the rotation calculation. The controller will assume that the error in the prediction is from the previous cycle, rather than from the previous update. This can make the adjustment to the ramp rate too dramatic.

The rotation factor should be divided by the update frequency (in cycles) if known. If the update frequency is unknown or cannot be approximated, then user calculations could be used to calculate the rotation factor at the time it is needed.

? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? 2015.9.30