Finding an impulse response function using genetic programming   [GP]

by

Keane, M., A., Koza, J., R. and Rice, J., P.

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Info: Proceedings of the 1993 American Control Conference (Conference proceedings), 1993, p. 2345-2350
Keywords:genetic algorithms, genetic programming
Abstract:
For many practical problems of control engineering, [CE] it is desirable to find a function, such as the impulse response function or transfer function, for a system for which one does not have an analytical model. The finding of the function, in symbolic form, that satisfies the requirements of the problem (rather than merely finding a single point) is usually not possible when one does not have an analytical model of the system. This paper illustrates how the recently developed genetic programming paradigm, [GP] can be used to find an approximation to the impulse response, in symbolic form, for a linear time-invariant system using only the observed response of the system to a particular known forcing function. The method illustrated can then be applied to other problems in control engineering [CE] that require the finding of a function in symbolic form.
Author(s) DL:Online papers for Koza, J., R.
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BibTex:
@InProceedings{keane:1993:firf,
  author =       "Martin A. Keane and John R. Koza and James P. Rice",
  title =        "Finding an impulse response function using genetic
                 programming",
  booktitle =    "Proceedings of the 1993 American Control Conference",
  year =         "1993",
  volume =       "III",
  pages =        "2345--2350",
  address =      "Evanston, IL, USA",
  organisation = "American Automatic Control Council",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "For many practical problems of control engineering, it
                 is desirable to find a function, such as the impulse
                 response function or transfer function, for a system
                 for which one does not have an analytical model. The
                 finding of the function, in symbolic form, that
                 satisfies the requirements of the problem (rather than
                 merely finding a single point) is usually not possible
                 when one does not have an analytical model of the
                 system. This paper illustrates how the recently
                 developed genetic programming paradigm, can be used to
                 find an approximation to the impulse response, in
                 symbolic form, for a linear time-invariant system using
                 only the observed response of the system to a
                 particular known forcing function. The method
                 illustrated can then be applied to other problems in
                 control engineering that require the finding of a
                 function in symbolic form.",
}