Detail publikace

Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control

PIVOŇKA, P. VELEBA, V. OŠMERA, P.

Originální název

Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

The new approach to analysis of on-line identification methods based on one-step-ahead prediction clears up their sensitivity to disturbances in control loop and explain why should be neural network based identification better then classical by using of short sampling period. The use of short sampling period in adaptive control has not been described properly when controlling the real process by adaptive controller. On one hand faster disturbance rejection due to short sampling period can be an advantage but on the other hand it brings us some practical problems. Particularly, quantization error and finite numerical precision of industrial controller must be considered in the real process control. We concentrate our attention on dealing with adverse effects that work on real-time identification of process, especially quantization. It is shown; that a neural network applied to on-line identification process produces more stable solution in the rapid sampling.

Klíčová slova

Rapid sampling domain, Neural networks for identification, Comparison of identifications methods

Autoři

PIVOŇKA, P.; VELEBA, V.; OŠMERA, P.

Rok RIV

2007

Vydáno

23. 7. 2007

Nakladatel

WSEAS

Místo

Řecko

ISBN

978-960-8457-90-4

Kniha

Systems Theory and Applications

Edice

Vol. 2.

Číslo edice

1.

Strany od

217

Strany do

222

Strany počet

6

BibTex

@inproceedings{BUT28312,
  author="Petr {Pivoňka} and Václav {Veleba} and Pavel {Ošmera}",
  title="Using of Neural Network Based Identification for Short Sampling Period in Adaptive Control",
  booktitle="Systems Theory and Applications",
  year="2007",
  series="Vol. 2.",
  number="1.",
  pages="217--222",
  publisher="WSEAS",
  address="Řecko",
  isbn="978-960-8457-90-4"
}