Genetic programming based approaches to identification and fault diagnosis of non-linear dynamic systems

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@Article{witczak:2002:IJC,
  author =       "Marcin Witczak and Andrzej Obuchowicz and 
                 Jozef Korbicz",
  title =        "Genetic programming based approaches to identification
                 and fault diagnosis of non-linear dynamic systems",
  journal =      "International Journal of Control",
  year =         "2002",
  volume =       "75",
  number =       "13",
  pages =        "1012--1031",
  month =        sep,
  email =        "M.Witczak@issi.uz.zgora.pl",
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1366-5820",
  DOI =          "doi:10.1080/00207170210156224",
  abstract =     "System identification is one of the most important
                 research directions. It is a diverse field which can be
                 employed in many different areas. One of them is the
                 model-based fault diagnosis. Thus, the problems of
                 system identification and fault diagnosis are closely
                 related. Unfortunately, in both the cases, the research
                 is strongly oriented towards linear systems, while the
                 problem of identification and fault diagnosis of
                 non-linear dynamic systems remains still open. There
                 are, of course, many more or less sophisticated
                 approaches to this problem, although they are not as
                 reliable and universal as those related to linear
                 systems, and the choice of the method to be used
                 depends on the application. The purpose of this paper
                 is to provide a new system identification framework
                 based on a genetic programming technique.Moreover, a
                 fault diagnosis scheme for non-linear systems is
                 proposed. In particular, a new fault detection observer
                 is presented , and the Lyapunov approach is used to
                 show that the proposed observer is convergent under
                 certain conditions. It is also shown how to use the
                 genetic programming technique to increase the
                 convergence rate of the observer. The final part of
                 this paper contains numerical examples concerning
                 identification of chosen parts of the evaporation
                 station at the Lublin Sugar Factory S.A., as well as
                 state estimation and fault diagnosis of an induction
                 motor.",
  notes =        "Evaporator and electrical induction motor Lubin Sugar
                 Factory November 1998 GP better than ARX (p1024)

                 Entry combined with witobu02",
}

Genetic Programming entries for Marcin Witczak Andrzej Obuchowicz Jozef Korbicz

Citations