Detail publikace

Adaptive Controllers by Using Neural Network Based Identification for Short Sampling Period

PIVOŇKA, P. VELEBA, V.

Originální název

Adaptive Controllers by Using Neural Network Based Identification for Short Sampling Period

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální abstrakt

The use of short sampling period in adaptive control has not been described properly when controlling the real process by adaptive controller. 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. 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 domain.

Klíčová slova

Adaptive Controllers, Neural Networks for Identification, Comparison of Identifications methods, Rapid Sampling Domain.

Autoři

PIVOŇKA, P.; VELEBA, V.

Rok RIV

2008

Vydáno

12. 3. 2008

Nakladatel

www.naun.org

Místo

USA

ISSN

1998-0140

Periodikum

INTERNATIONAL JOURNAL of MATHEMATICAL MODELS AND METHODS IN APPLIED SCIENCES

Ročník

1

Číslo

1

Stát

Spojené státy americké

Strany od

62

Strany do

67

Strany počet

6

URL

http://www.naun.org

BibTex

@article{BUT44826,
  author="Petr {Pivoňka} and Václav {Veleba}",
  title="Adaptive Controllers by Using Neural Network Based Identification for Short Sampling Period",
  journal="INTERNATIONAL JOURNAL of MATHEMATICAL MODELS AND METHODS IN APPLIED SCIENCES",
  year="2008",
  volume="1",
  number="1",
  pages="62--67",
  issn="1998-0140",
  url="http://www.naun.org"
}