NDLI: Steady-state identification with gross errors for industrial process units

Content Provider	IEEE Xplore Digital Library
Author	Lili Tao Chaochun Li Xiangdong Kong Feng Qian
Copyright Year	2012
Description	Author affiliation: Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai 200237, China (Lili Tao; Chaochun Li; Xiangdong Kong; Feng Qian)
Abstract	Identification of steady state is an important task for satisfactory control of many processes. Due to the disadvantages of the traditional steady-state identification (SSI) methods, the adaptive polynomial filtering (APF) method was used for SSI in this paper. Furthermore, the presence of gross errors can corrupt the steady-state identification method, giving undesirable results. The APF steady-state identification with the new 3δ formula method was modified for gross errors detection by using the quartile method based on first order differential in this paper. This method was applied to the simulated data and data from a crude oil distillation unit. Simulation results and comparisons with the traditional methods confirmed the validity of the proposed method.
Starting Page	4151
Ending Page	4154
File Size	113107
Page Count	4
File Format	PDF
ISBN	9781467313971
e-ISBN	9781467313988
DOI	10.1109/WCICA.2012.6359172
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-07-06
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Steady-state Polynomials Filtering Measurement uncertainty Noise measurement Process control Market research First order differential Steady-State Identification Gross error Adaptive polynomial filtering
Content Type	Text
Resource Type	Article

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