System Identification

Abstract

System identification has its roots in standard statistical techniques and many of the basic routines have direct interpretations as well known statistical methods such as least squares and maximum likelihood. The control community took an active part in the development and application of these basic techniques to dynamic systems right after the birth of “modern control theory” in the early 1960s. Maximum likelihood estimation was applied to difference equations (ARMAX models) by Åström and Bohlin (1965) and thereafter a wide range of estimation techniques and model parameterizations flourished. By now, the area is well matured with established and well-understood techniques. Industrial use and application of the techniques has become standard. See Ljung (2007) for a common software package.

Cite this paper

@incollection{anon2018system,
  title = {{System Identification}},
  pages = {1303--1344},
  year = {2018},
  doi = {10.1201/b10384-126}
}

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