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Arief Baihaqi
Faculty of Science, Department of Mathematic. Institut Teknologi Sepuluh Nopember, Kampus Keputih Sukolilo Surabaya
Industrial & Manufacturing Engineering

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The Reduced Rank of Ensemble Kalman Filter to Estimate the Temperature of Non Isothermal Continue Stirred Tank Reactor Apriliani, Erna; Adzkiya, Dieky; Baihaqi, Arief
Jurnal Teknik Industri Vol 13, No 2 (2011): DECEMBER 2011
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (296.561 KB) | DOI: 10.9744/jti.13.2.107-112

Abstract

Kalman filter is an algorithm to estimate the state variable of dynamical stochastic system. The square root ensemble Kalman filter is an modification of Kalman filter. The square root ensemble Kalman filter is proposed to keep the computational stability and reduce the computational time. In this paper we study the efficiency of the reduced rank ensemble Kalman filter. We apply this algorithm to the non isothermal continue stirred tank reactor problem. We decompose the covariance of the ensemble estimation by using the singular value decomposition (the SVD), and then we reduced the rank of the diagonal matrix of those singular values. We make a simulation by using Matlab program. We took some the number of ensemble such as 100, 200 and 500. We compared the computational time and the accuracy between the square root ensemble Kalman filter and the ensemble Kalman filter. The reduced rank ensemble Kalman filter can’t be applied in this problem because the dimension of state variable is too less.
Co-Authors Dieky Adzkiya Erna Apriliani