= Measurement noise
{title2=$n(t)$}
<Measurement noise> is a fluctuating contribution to <measurement error>. An additive model for a <measured output> is $y_m(t)=y(t)+n(t)$, where $y$ is the actual <plant output>. A <controller> using <feedback control> can react to $n$ as though it were a change in the <plant output>. This effect is absent from the ideal noiseless examples under <control theory>; an <errors-in-variables model> represents a related distinction between latent quantities and their noisy observations.
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