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1. AU2003237734 - Dynamic on-line optimization of production processes

Office
Australie
Numéro de la demande 2003237734
Date de la demande 12.06.2003
Numéro de publication 2003237734
Date de publication 11.09.2003
Type de publication A
CIB
G05B 13/04
GPHYSIQUE
05COMMANDE; RÉGULATION
BSYSTÈMES DE COMMANDE OU DE RÉGULATION EN GÉNÉRAL; ÉLÉMENTS FONCTIONNELS DE TELS SYSTÈMES; DISPOSITIFS DE CONTRÔLE OU DE TEST DE TELS SYSTÈMES OU ÉLÉMENTS
13Systèmes de commande adaptatifs, c. à d. systèmes se réglant eux-mêmes automatiquement pour obtenir un rendement optimal suivant un critère prédéterminé
02électriques
04impliquant l'usage de modèles ou de simulateurs
D21G 9/00
DTEXTILES; PAPIER
21FABRICATION DU PAPIER; PRODUCTION DE LA CELLULOSE
GCALANDRES; ACCESSOIRES POUR MACHINES À FABRIQUER LE PAPIER
9Autres accessoires pour machines à fabriquer le papier
CPC
D21G 9/0018
DTEXTILES; PAPER
21PAPER-MAKING; PRODUCTION OF CELLULOSE
GCALENDERS; ACCESSORIES FOR PAPER-MAKING MACHINES
9Other accessories for paper-making machines
0009Paper-making control systems
0018controlling the stock preparation
G05B 13/048
GPHYSICS
05CONTROLLING; REGULATING
BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
13Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
02electric
04involving the use of models or simulators
048using a predictor
Déposants ABB AB
Inventeurs Kallen, Lennart
Ledung, Lars
Lindberg, Tomas
Persson, Ulf
Sahlin, Per-Olof
Données relatives à la priorité 0201812 12.06.2002 SE
Titre
(EN) Dynamic on-line optimization of production processes
Abrégé
(EN) A process is modeled by a dynamic model, handling time dependent relations between manipulated variables of different process sections (10A-D) and measured process output variables. Suggested input trajectories for manipulated variables for a subsequent time period are obtained by optimizing an objective function over a prediction time period, under constraints imposed by the dynamic process model and/or preferably a production plan for the same period. The objective function comprises relations involving predictions of controlled process output variables as a function of time using the process model, based on the present measurements, preferably by a state estimation procedure. By the use of a prediction horizon, also planned future operational changes can be prepared for, reducing any induced fluctuations. In pulp and paper processes, process output variables associated with chemical additives can be used, adapting the optimization to handle chemical additives aspects.