Modelling and identification of linear discrete systems using least squares method
Peter Šarafín, Martin Hudik, Martin Revák, Peter Ševčík, Samuel Žák
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 891–894 (2017)
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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