Detail publikace

Advantages of Neural Networks in Adaptive Control

SCHMIDT, M., PIVOŇKA, P.

Originální název

Advantages of Neural Networks in Adaptive Control

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper discusses the problems adaptive controllers have to face when working with a sampling period that is significantly shorter than the global time constant of the controlled system. A short sampling period is beneficial for disturbance cancellation, but it makes on-line identification of the system difficult in the presence of quantization effect, noise and disturbances. Neural networks present a promising approach to solving the problem. However, there remains a problem with extracting useful information about the system's dynamics in the form of training patterns for commonly used regressive models. Ways to enrich the training patterns with information about the system's behaviour are discussed.

Klíčová slova

Adaptive Control, Neural Networks for Identification

Autoři

SCHMIDT, M., PIVOŇKA, P.

Rok RIV

2006

Vydáno

1. 10. 2006

Nakladatel

Rektor der Hochschule Zittau/Gorlitz

Místo

Zittau

ISBN

3-9808089-8-X

Kniha

13th Zittau Fuzzy Coloquium

Strany od

75

Strany do

80

Strany počet

6

BibTex

@inproceedings{BUT19696,
  author="Michal {Schmidt} and Petr {Pivoňka}",
  title="Advantages of Neural Networks in Adaptive Control",
  booktitle="13th Zittau Fuzzy Coloquium",
  year="2006",
  pages="6",
  publisher="Rektor der Hochschule Zittau/Gorlitz",
  address="Zittau",
  isbn="3-9808089-8-X"
}