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