Generalized Predictive Control with a Non-linear Autoregressive Model

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F05%3APU47654" target="_blank" >RIV/00216305:26220/05:PU47654 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Generalized Predictive Control with a Non-linear Autoregressive Model

Original language description

This paper presents a solution to computation of predictive control using non-linear auto-regressive models. For the non-linear model a neural network is used as a perspective tool for modelling of dynamic systems. However, the described approach is applicable to any type of auto-regressive model. The model is not linearized in the operating point, but in each control optimization step the model's derivative is computed (linearization) for all points in the prediction horizon. The method can be usedd inreal-time control. This is verified by porting the algorithm directly to the PLC.

Czech name

Prediktiví regulátor s nelineárním autpregresivním modelem

Czech description

Článek se zabývá výpočtem prediktivního regulátoru s použitím nelineárního autoregresivního modelu na bázi neuronové sítě. Použitý algoritmus pracuje v reálném čase.

Type

D - Article in proceedings

CEP classification

JB - Sensors, detecting elements, measurement and regulation

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)

Publication year

2005

Confidentiality

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

Article name in the collection

Automatic Control Modeling and Simulation

ISBN

960-8457-12-2

ISSN

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e-ISSN

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Number of pages

5

Pages from-to

85-89

Publisher name

WSEAS

Place of publication

Praha

Event location

Praha

Event date

Mar 13, 2005

Type of event by nationality

EUR - Evropská akce

UT code for WoS article

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