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1. AU2014273550 - Process control method

Office
Australia
Application Number 2014273550
Application Date 15.05.2014
Publication Number 2014273550
Publication Date 12.11.2015
Publication Kind B2
IPC
G05B 13/04
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
CPC
G05B 13/042
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
042in which a parameter or coefficient is automatically adjusted to optimise the performance
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
Applicants Core A/S
Inventors
Agents Pipers Intellectual Property
Title
(EN) Process control method
Abstract
(EN)
The invention relates to method for controlling a process, the method comprising an adaptive control model and at least one process input and at least one process output, the control model comprising predicting the relevant targets in the process; and selecting the relevant drivers for the process based on the target prediction, where the method preferably comprises adapting a number of parameters based on one or more inputs, and using the adapted parameters as an input for the target prediction.