MATLAB CONTROL SYSTEM TOOLBOX 9 Specifiche Pagina 240

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10 Design Case Studies
10-56
xlabel('No. of samples'), ylabel('Error')
The first plot shows the true response (dashed line) and the filtered output
(solid line). The second plot compares the measurement error (dash-dot)
with the estimation error (solid). This plot shows that the noise level has been
significantly reduced. This is confirmed by the following error covariance
computations.
MeasErr = y-yv;
MeasErrCov = sum(MeasErr.*MeasErr)/length(MeasErr);
EstErr = y-ye;
EstErrCov = sum(EstErr.*EstErr)/length(EstErr);
The error covariance before filtering (measurement error) is
MeasErrCov
MeasErrCov =
1.1138
while the error covariance after filtering (estimation error) is only
y
y
e
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