Multivariable Least Squares Frequency Domain Identification using Polynomial Matrix Fraction Descriptions
نویسندگان
چکیده
In this paper an approach is presented to estimate a linear multivariable model on the basis of (noisy) frequency domain data via a curve tting procedure. The multivariable model is parametrized in either a left or a right polynomial matrix fraction description and the parameters are computed by using a two-norm minimization of a multivariable output error. Additionally, input-output or element-wise based multivariable frequency weightings can be speci ed to tune the curve tting error in a exible way. The procedure is demonstrated on experimental data obtained from a 3 input 3 output Wafer Stepper system.
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تاریخ انتشار 1996