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CONTROLADOR NEURO-ROBUSTO PARA SISTEMAS NO LINEALES

Authors: JOSÉ LUIS CALVO ROLLE; IVÁN MACHÓN GONZÁLEZ; HILARIO LÓPEZ GARCÍA;

CONTROLADOR NEURO-ROBUSTO PARA SISTEMAS NO LINEALES

Abstract

This work shows a new method to obtain the tuning parameters of a controller based on PID topology in standard format in order to lead the controlled system to a stable state. This technique is based on the well known Gain Scheduling method. Firstly, the system is identified for each key operating point obtaining the corresponding transfer functions by means of least squares techniques. Then the stability structures are calculated using the transfer functions aiming to train an artificial neural network which prevents the system from becoming unstable. Finally, the proposed method is experimentally verified on a laboratory plant.

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Powered by OpenAIRE graph
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Average
Top 10%
Average
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