A proportional controller based on clustering theory: an academic example of a machine learning discipline
Visualitza/Obre
10.1051/matecconf/201821002005
Inclou dades d'ús des de 2022
Cita com:
hdl:2117/123077
Tipus de documentText en actes de congrés
Data publicació2018
EditorEDP Sciences
Condicions d'accésAccés obert
Llevat que s'hi indiqui el contrari, els
continguts d'aquesta obra estan subjectes a la llicència de Creative Commons
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Reconeixement 3.0 Espanya
Abstract
The main objective of this paper is to present a controller design based on the K-means clustering
theory. The controller is realized in such way that when the plant output is located outside of the designed
clustering set, the controller forces it to be in it. Moreover, and according to our real experiment applied
to stabilize an unstable integrator plant, our controller approach design is also robust against un-vanishing
perturbations and nonlinearity effects on the overall closed-loop system such as saturation, slew-rate limit, and
limit bandwidth frequency operation.
CitacióAcho, L., Buenestado, P. A proportional controller based on clustering theory: an academic example of a machine learning discipline. A: International Conference on Circuits, Systems, Communications and Computers. "CSCC 2018: 22nd International Conference on Circuits, Systems, Communications and Computers: Mallorca, Spain: July 14-17, 2018: proceedings book". EDP Sciences, 2018, p. 1-3.
ISBN2261-236X
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matecconf_cscc2018_02005 (1).pdf | paper | 375,2Kb | Visualitza/Obre |