Genetic programming based observers for nonlinear systems

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Marcin Witczak and Jozef Korbicz",
  title =        "Genetic programming based observers for nonlinear
  booktitle =    "4th IFAC Symposium on Fault Detection Supervision and
                 Safety for Technical Processes : Safeprocess 2000",
  year =         "2000",
  volume =       "2",
  pages =        "967--972",
  address =      "Budapest, Hungary",
  month =        jun # " 14-16",
  keywords =     "genetic algorithms, genetic programming, fault
                 detection, nonlinear systems, model approximation,
  ISSN =         "1474-6670",
  URL =          "",
  DOI =          "doi:10.1016/S1474-6670(17)37483-9",
  size =         "6 pages",
  abstract =     "Model-based approaches to fault detection and
                 isolation suffer from the inconvenience that in
                 practice it is often difficult to obtain an accurate
                 mathematical model of a nonlinear system of interest. A
                 way out of this problem is to use data-driven
                 approaches to model the process input-output behaviour.
                 In this work, a relatively new genetic programming
                 technique is employed to design a nonlinear observer
                 which models the juice temperature at the outlet of an
                 evaporator at the Lublin Sugar Factory in Poland. The
                 resulting observer is then used to generate a residual
                 for fault detection.",
  notes =        "Sep 2018 Elsevier doi: gives page numbers as

                 Also known as \cite{WITCZAK2000945}",

Genetic Programming entries for Marcin Witczak Jozef Korbicz