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Detail publikace
Pivoňka, P., Veleba, V., Ošmera, P.
Originální název
Adaptive Controllers by Using Neural Network Based Identification for Short Sampling Period
Typ
článek ve sborníku ve WoS nebo Scopus
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
Rok RIV
2006
Vydáno
5. 12. 2006
Nakladatel
Nanyang Technological University
Místo
Singapore
ISBN
1-4244-0342-1
Kniha
9th International Conference on Control, Automation, Robotics and Vision, IEEE ICARCV2006
Strany od
521
Strany do
526
Strany počet
6
BibTex
@inproceedings{BUT22106, author="Petr {Pivoňka} and Václav {Veleba}", title="Adaptive Controllers by Using Neural Network Based Identification for Short Sampling Period", booktitle="9th International Conference on Control, Automation, Robotics and Vision, IEEE ICARCV2006", year="2006", pages="6", publisher="Nanyang Technological University", address="Singapore", isbn="1-4244-0342-1" }