Please use this identifier to cite or link to this item:https://hdl.handle.net/20.500.12259/42976
Type of publication: Straipsnis Clarivate Analytics Web of Science ar/ir Scopus / Article in Clarivate Analytics Web of Science or / and Scopus (S1)
Field of Science: Informatikos inžinerija / Informatics engineering (T007)
Author(s): Kaminskas, Vytautas;Liaučius, Gediminas
Title: Predictor-based self-tuning control of pressure plants
Is part of: Informacinės technologijos ir valdymas = Information technology and control. Kaunas : Technologija, 2014, t. 43, Nr. 4
Extent: p. 447-454
Date: 2014
Keywords: Self-tuning control;Predictor-based;Minimum-phase model;Nonminimum-phase model;Factorization;Pressure plant
Abstract: A digital predictor-based self-tuning control with constraints for the pressure plants, which is able to cope with minimum-phase and nonminimum-phase plant models is presented in this paper. Determined that applying polynomial factorization for such models the characteristic polynomials of closed-loops are changed. Therefore, the on-line identification of the models’ parameters is so performed that ensures stable closed-loops. A choice of the sampling period in digital control typically impacts a control quality of the plant, thus we propose a method for optimization of a sampling period in the digital predictor-based self-tuning control system. The impact of the selection of the sampling period and input signals’ constraints – amplitude boundaries and the change rate - to the control quality of the pressure plant was experimentally analysed
Internet: http://www.itc.ktu.lt/index.php/ITC/article/view/8742
Affiliation(s): Informatikos fakultetas
Sistemų analizės katedra
Vytauto Didžiojo universitetas
Appears in Collections:Universiteto mokslo publikacijos / University Research Publications

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