کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
689098 | 889590 | 2013 | 17 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multiple model approach to nonlinear system identification with an uncertain scheduling variable using EM algorithm
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
تکنولوژی و شیمی فرآیندی
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![عکس صفحه اول مقاله: Multiple model approach to nonlinear system identification with an uncertain scheduling variable using EM algorithm Multiple model approach to nonlinear system identification with an uncertain scheduling variable using EM algorithm](/preview/png/689098.png)
چکیده انگلیسی
This paper deals with system identification of general nonlinear dynamical systems with an uncertain scheduling variable. A multi model approach is developed; wherein, a set of local auto regressive exogenous (ARX) models are first identified at different process operating points, and are then combined to describe the complete dynamics of a nonlinear system. An expectation-maximization (EM) algorithm is used for simultaneous identification of local ARX models, and for computing the probability associated with each of the local ARX models taking effect. A smoothing algorithm is used to estimate the distribution of the hidden scheduling variables in the EM algorithm. If the dynamics of the scheduling variables are linear, Kalman smoother is used; whereas, if the dynamics are nonlinear, sequential Monte-Carlo (SMC) method is used. Several simulation examples, including a continuous stirred tank reactor (CSTR) and a distillation column, are considered to illustrate the efficacy of the proposed method. Furthermore, to highlight the practical utility of the developed identification method, an experimental study on a pilot-scale hybrid tank system is also provided.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Process Control - Volume 23, Issue 10, November 2013, Pages 1480-1496
Journal: Journal of Process Control - Volume 23, Issue 10, November 2013, Pages 1480-1496
نویسندگان
Lei Chen, Aditya Tulsyan, Biao Huang, Fei Liu,