Adaptive Controllers by Using Neural Network Based Identification for Short Sampling Period
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F06%3APU63746" target="_blank" >RIV/00216305:26220/06:PU63746 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Adaptive Controllers by Using Neural Network Based Identification for Short Sampling Period
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BC - Theory and management systems
OECD FORD branch
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Result continuities
Project
<a href="/en/project/GA102%2F06%2F1132" target="_blank" >GA102/06/1132: Softcomputing in Control</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)
Others
Publication year
2006
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
9th International Conference on Control, Automation, Robotics and Vision, IEEE ICARCV2006
ISBN
1-4244-0342-1
ISSN
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e-ISSN
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Number of pages
6
Pages from-to
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Publisher name
Nanyang Technological University
Place of publication
Singapore
Event location
Singapore
Event date
Dec 5, 2006
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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