On a parameter adaptive self-organizing system in the presence of large outliers in observations
Articles
Rimantas Pupeikis
Institute of Mathematics and Informatics
Published 2009-12-20
https://doi.org/10.15388/LMR.2009.68
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Keywords

self-tuning controller
the minimum variance control law
parametric identification
outliers

How to Cite

Pupeikis R. (2009) “On a parameter adaptive self-organizing system in the presence of large outliers in observations”, Lietuvos matematikos rinkinys, 50(proc. LMS), pp. 386–390. doi: 10.15388/LMR.2009.68.

Abstract

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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