On a parameter adaptive self-organizing system in the presence of large outliers in observations | Zendy

Rimantas Pupeikis | Zendy

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On a parameter adaptive self-organizing system in the presence of large outliers in observations

Author(s) -

Rimantas Pupeikis

Publication year - 2009

Publication title -

lietuvos matematikos rinkinys

Language(s) - English

Resource type - Journals

eISSN - 2335-898X

pISSN - 0132-2818

DOI - 10.15388/lmr.2009.68

Subject(s) - outlier , lti system theory , control theory (sociology) , gaussian , computer science , noise (video) , controller (irrigation) , variance (accounting) , invariant (physics) , gaussian noise , signal (programming language) , linear system , adaptive control , algorithm , mathematics , control (management) , artificial intelligence , mathematical analysis , mathematical physics , agronomy , physics , accounting , quantum mechanics , business , image (mathematics) , biology , programming language

The aim of the given paper is development of a minimum variance control (MVC) approach for a closed-loopdiscrete-time linear time-invariant (LTI) system when the parameters of a dynamic system as well as that of a controller are not known and ought to be estimated by processing observations in the case of additive Gaussian noise on the output with contaminating outliers uniformly spread in it. Afterwards, the current value of the control signal is found in each operation, and it is used to generate the output of the system. The results of numerical simulation by computer are presented and discussed here, too.

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