Title :
Dynamic system calibration by system identification methods
Author :
Ergon, R. ; Di Ruscio, D.
Author_Institution :
Telemark Inst. of Technol., Porsgrunn, Norway
Abstract :
Primary output variables from industrial processes can be estimated from known input variables and secondary process measurements. As a basis for this, the dynamic predictor has to be identified from data collected during a calibration experiment. In this paper, the theoretical basis for this is investigated, and a systematic experimental method is proposed.
Keywords :
calibration; identification; predictive control; process control; calibration experiment; dynamic predictor; dynamic system calibration; industrial processes; known input variables; primary output variables; secondary process measurements; system identification methods; Calibration; Estimation; Kalman filters; Mathematical model; Noise; Noise measurement; Predictive models; Estimation; multivariate calibration; system identification;
Conference_Titel :
Control Conference (ECC), 1997 European
Conference_Location :
Brussels
Print_ISBN :
978-3-9524269-0-6
