Multivariable Least Squares Frequency Domain Identi cation using Polynomial Matrix Fraction Descriptions

@inproceedings{Callafon1996MultivariableLS,
  title={Multivariable Least Squares Frequency Domain Identi cation using Polynomial Matrix Fraction Descriptions},
  author={Raymond A. de Callafon and D. de Roover and Paul M. J. Van den Hof},
  year={1996}
}
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… CONTINUE READING
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