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볼테라 시리즈 입력을 이용한 냉연 산세 라인 산농도 모델 추정
박찬은(Chan Eun Park),송주만(Ju-man Song),박태수(Tae Su Park),노일환(Il-Hwan Noh),박형국(Hyoung-Kuk Park),최승갑(Seung Gab Choi),박부견(PooGyeon Park) 제어로봇시스템학회 2015 제어·로봇·시스템학회 논문지 Vol.21 No.12
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.