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Polish Information Processing Society
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Annals of Computer Science and Information Systems, Volume 11

Proceedings of the 2017 Federated Conference on Computer Science and Information Systems

Modelling and identification of linear discrete systems using least squares method

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DOI: http://dx.doi.org/10.15439/2017F406

Citation: Proceedings of the 2017 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 11, pages 891894 ()

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Abstract. In control applications, we often encounter systems that respond to the change of control signal in an undesirable way. To adjust system output, there arises the need to know system parameters, so the identification has to be performed. The aim of this paper is to compare upstanding identification error that is the consequence of dataset size, input signal type, and quantization error occurring in the signal. The experimental part of this paper presents the results measured on the real device and shows the identification results.

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