Abstract
Using nonparametric noise models the complexity of the errors-in-variables problem is reduced to that of a generalised output error problem. Via experiments with periodic excitation signals one can easily obtain nonparametric estimates of the input-output noise models in a preprocessing step. The following assumptions are hereby made: (i) the system operates in steady state, (ii) at least P = 7 signal periods are available, and (iii) consecutive signal periods are independently distributed. Due to the noise colouring, assumption (iii) is an approximation. In addition assumptions (i) and (ii) reduce the frequency resolution of the experiment. In this paper we present a method that handles these three restrictions: 2 periods of the transient response to a periodic excitation are sufficient, and the correlation among consecutive signal periods is suppressed.
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