Robustifying an extended unknown input observer with genetic programming

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@InProceedings{witkor01a,
  author =       "Marcin Witczak and Jozef Korbicz",
  title =        "Robustifying an extended unknown input observer with
                 genetic programming",
  booktitle =    "Methods and Models in Automation and Robotics - MMAR
                 2001 : Proceedings of the 7th IEEE International
                 Conference",
  year =         "2001",
  volume =       "2",
  pages =        "1061--1066",
  publisher =    "Wydaw. Uczelniane Politechniki Szczeci\~{n}skiej",
  email =        "M.Witczak@issi.uz.zgora.pl",
  keywords =     "genetic algorithms, genetic programming",
  abstract =     "This paper is focused on the problem of designing
                 nonlinear observers for fault diagnosis tasks.The main
                 objective is to show how to employ a modified version
                 of the well-known unknown inputobserver, which can be
                 applied to linear stochastic systems, to form a
                 nonlinear deterministic observer. Moreover, it is shown
                 that the convergence of the proposed observer is
                 ensured under certain conditions. In particular an
                 unknown diagonal matrix is introduced in order to take
                 the linearization errors into account, and then the
                 Lyapunov method is employed to obtain the convergence
                 conditions . The final part of this paper shows how to
                 use a genetic programming technique to increase the
                 convergence rate of the proposed observer.",
}

Genetic Programming entries for Marcin Witczak Jozef Korbicz

Citations