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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.
An improved stability criteria for neutral-type Lur’e systems with time-varying delays
Park, JunMin,Lee, Seok Young,Park, PooGyeon Elsevier 2018 Journal of the Franklin Institute Vol.355 No.12
<P><B>Abstract</B></P> <P>This paper improves stability criteria for neutral-type Lur’e systems with time-varying delays, where the nonlinearity satisfies sector and slope restrictions. A proposed Lyapunov–Krasovskii functional consisting of a quadratic term and integral terms for the time-varying delays and the nonlinearities, has four different characteristics. First, the quadratic term utilizes not only the current and delayed states but also the nonlinear vectors. Second, the integral terms for nonlinearities fully exploit the characteristics of sector and slope restrictions. Third, the integral terms for nonlinearities also exploit the characteristic of incremental restriction induced from the slope restriction. Fourth, this paper utilizes a vector related to the time derivative of the neutral delayed state to handle the neutral delay. Based on the proposed Lyapunov–Krasovskii functional, the improved stability criteria are derived in terms of linear matrix inequalities. Numerical examples show that the proposed criteria present less conservative results than the previous criteria.</P>
Scheduled-Stepsize NLMS Algorithm
Poogyeon Park,Moonsoo Chang,Namwoong Kong IEEE 2009 IEEE signal processing letters Vol.16 No.12
<P>This paper presents a method of scheduling stepsizes for the normalized least-mean-squares (SS-NLMS) algorithm. Geometrically interpreting the mean square deviation (MSD) learning curve leads to establishing an objective curve and to constructing a lookup table of stepsizes in order for the MSD to follow the curve. The SS-NLMS shows not only good performance but also robustness with respect to different signal-to-noise ratio (SNR) in measurement noise and different correlation in input signals with a very small number of online computations. Moreover, the scalability of the tabled stepsize with respect to the number of taps is described. For the efficient memory usage in practice, a modified version replaces the tabled stepsizes by down-sampled stepsizes with no performance degradation.</P>