Publisher : Institute of Control, Robotics and Systems
DOI : 10.5302/J.ICROS.2015.15.0088
Title & Authors
Estimation of Acid Concentration Model of Cooling and Pickling Process Using Volterra Series Inputs Park, Chan Eun; Song, Ju-man; Park, Tae Su; Noh, Il-Hwan; Park, Hyoung-Kuk; Choi, Seung Gab; Park, PooGyeon;
This paper deals with estimating the acid concentration of pickling process using the Volterra inputs. To estimate the acid concentration, the whole pickling process is represented by the grey box model consists of the white box dealing with known system and the black box dealing with unknown system. Because there is a possibility of nonlinear term in the unknown system, the Volterra series are used to estimate the acid concentration. For the white box modeling, the acid tank solution level and concentration equations are used, and for the black box modeling, the acid concentration is estimated using the Volterra Least Mean Squares (LMS) algorithm and Least Squares (LS) algorithm. The LMS algorithm has the advantage of the simple structure and the low computation, and the LS algorithm has the advantage of lowest error. The simulation results compared to the measured data are included.
steel pickling process;Volterra filter;least mean squares;least squares;nonlinear model;
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