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With feedback only, on the other hand, the variance of y is simply<br />

in the frequency domain and<br />

|Y(f)| 2 = |Tywt(f)| 2 Swtwt (f) (220)<br />

Var(y) =<br />

∞<br />

−∞<br />

|Tywt(f)| 2 Swtwt (f)df (221)<br />

in the time domain. Section 10.2.3 provides an explanation for treating reduction in variance<br />

as a control objective.<br />

By comparing Eq. (218) with Eq. (220), the frequencies where feedforward control with<br />

ˆwt = wm is beneficial can be found. Ideal feedforward control with no prefilter reduces the<br />

variance of y at the frequencies where Eq. (222) is satisfied:<br />

Swtwt (f)+Swmwm (f)−2ℜ{Swtwm (f)} < Swtwt (f). (222)<br />

Equation (222) can be rearranged as<br />

1<br />

2 < ℜ{Swtwm (f)}<br />

. (223)<br />

Swmwm (f)<br />

10.2.2 Feedforward Control with Imperfect Measurements<br />

By introducing a prefilter Hpre, shown in Fig. 134, to form an estimate of wt based on the<br />

measured wm, the variance of the output variable y can be reduced below the value without<br />

prefiltering so that feedforward control is always an improvement over feedback only (Simley<br />

and Pao, 2013b). With prefiltering, the output variable y is given as<br />

In the frequency domain, the variance of y is given by<br />

y = Tywt(wt −Hprewm). (224)<br />

|Y(f)| 2 = |Tywt(f)| 2 |Wt(f)−Hpre(f)Wm(f)| 2 . (225)<br />

The optimal prefilter should minimize the variance of y in Eq. (225) at all frequencies. The<br />

classical solution to this minimization problem is the transfer function<br />

Hpre(f) = Swtwm (f)<br />

. (226)<br />

Swmwm (f)<br />

When the optimal minimum-variance prefilter is employed, the variance of y in the frequency<br />

domain reduces to<br />

|Y(f)| 2 = |Tywt(f)| 2 Swtwt (f) 1−γ 2 wtwm (f)<br />

(227)<br />

where γ2 (f) is the coherence function between the true wind disturbance and the lidar<br />

wtwm<br />

measurement. The coherence function describes the correlation between two signals as a<br />

function of frequency, with an output of 0 indicating no correlation and 1 describing perfect<br />

correlation. The coherence between signals a(t) and b(t) is defined as<br />

γ 2 ab(f) =<br />

2<br />

|Sab(f)|<br />

. (228)<br />

Saa(f)Sbb(f)<br />

Eq. (227) reveals that when measurement coherence is 1 (perfect correlation), the variance<br />

of y can be reduced to zero. When measurement coherence is 0 (the measurement contains<br />

no information about the true disturbance), on the other hand, feedforward control is not<br />

used and the variance of y reduces to the feedback only case (Eq. (220)).<br />

Inreality,theoptimalprefilterdefinedbyEq.(226)cannotberealizedbecauseofconstraints<br />

on the preview time available to the filter (Simley and Pao, 2013b). Instead, the optimal filter<br />

can be calculated using time domain methods where the available preview time appears as a<br />

hard constraint. Further details on implementation of the optimal measurement filter can be<br />

found in Simley and Pao (2013b).<br />

<strong>DTU</strong> Wind Energy-E-Report-0029(EN) 197

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