Closed Loop On-Line Identification Based on Neural Networks in Adaptive Optimal Controller

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F02%3APU29163" target="_blank" >RIV/00216305:26220/02:PU29163 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Closed Loop On-Line Identification Based on Neural Networks in Adaptive Optimal Controller
Original language description
Last ten years, algorithms based on Neural Networks were used successfully for the pattern recognition, process control and system identification. Artificial Neural Networks applied this way have been strongly developing together with the classical control. It is mainly because of their self-learning property and wide-range of easy algorithm designs. Using Neural Networks for identification is well-known strategy where the process is observed usually through its input and output only. The real process iis often influenced by disturbances. In this case, the more identified transfer function is inaccurate the more as disturbance influences IO of the measured process. This paper shows a comparison between on-line identification (in the real time) based onNeural Networks and a classical identification implemented in adaptive optimal controller. The setting of the sampling period for the both identification methods is investigated.
Czech name
—
Czech description
—

Project
<a href="/en/project/GA102%2F01%2F1485" target="_blank" >GA102/01/1485: Enviroment for development, modelling and application of heterogenous systems</a><br>
Continuities
Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year
2002
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)