Time - domain Identi cation of DynamicErrors - in - variables Systems Using Periodic

The use of periodic excitation signals in identiication experiments is advocated. With periodic excitation it is possible to separate the driving signals and the disturbances , which for instance implies that the noise properties can be independently estimated. In the paper a non-parametric noise model, estimated directly from the measured data, is used in a compensation strategy applicable to both least squares and total least squares estimation. The resulting least squares and total least squares methods are applicable in the errors-in-variables situation and give consistent estimates regardless of the noise. The feasibility of the idea is illustrated in a simulation study.