Quantization Effect Influences Identification in Adaptive LQ Controller

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F03%3APU37332" target="_blank" >RIV/00216305:26220/03:PU37332 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Quantization Effect Influences Identification in Adaptive LQ Controller

Popis výsledku v původním jazyce

Many controlling algorithms were developed to satisfy designer's assumption that controlled process is stable, optimal, adaptive etc. Only few of them should be used in the real-time, on-line adaptation or implemented into Programmable Logic Controller.Algorithms based on neural networks were successfully tested as for the process control as for the process identification. In simulation, quantization effect given by A/D and D/A converter is very often left out. Quantization effect influences identifiedd process transfer function and controller possibilities. In this case, controller controls the process inaccurate and often with oscillations than without quantization. This paper shows a comparison between two identification methods. Online identification (in the real time) based on neural networks and a classical identification are implemented in adaptive LQ controller with three types of A/D and D/A converters at least be closer in simulation the real process controlling.

Název v anglickém jazyce

Quantization Effect Influences Identification in Adaptive LQ Controller

Popis výsledku anglicky

Many controlling algorithms were developed to satisfy designer's assumption that controlled process is stable, optimal, adaptive etc. Only few of them should be used in the real-time, on-line adaptation or implemented into Programmable Logic Controller.Algorithms based on neural networks were successfully tested as for the process control as for the process identification. In simulation, quantization effect given by A/D and D/A converter is very often left out. Quantization effect influences identifiedd process transfer function and controller possibilities. In this case, controller controls the process inaccurate and often with oscillations than without quantization. This paper shows a comparison between two identification methods. Online identification (in the real time) based on neural networks and a classical identification are implemented in adaptive LQ controller with three types of A/D and D/A converters at least be closer in simulation the real process controlling.

Druh

D - Stať ve sborníku

CEP obor

JB - Senzory, čidla, měření a regulace

OECD FORD obor

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Projekt

<a href="/cs/project/GA102%2F01%2F1485" target="_blank" >GA102/01/1485: Prostředí pro vývoj, modelování a aplikaci heterogenních systémů</a><br>

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2003

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

The 11th Mediterranean Conference on Control and Automation

ISBN

960-87706-0-2

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

77-82

Název nakladatele

Kostas J. Kyriakopoulos, National Technical University of Athens, Greece

Místo vydání

Rhodos, Řecko

Místo konání akce

Rhodes

Datum konání akce

18. 6. 2003

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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