دانلود A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems

ترجمه A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems
قیمت : 285,000 ریال
شناسه محصول : 2008787
نویسنده/ناشر/نام مجله : ISA Transactions
سال انتشار: 2017
تعداد صفحات انگليسي : 7
نوع فایل های ضمیمه : Pdf+Word
حجم فایل : 1 Mb
کلمه عبور همه فایلها : www.daneshgahi.com
عنوان انگليسي : A fast iterative recursive least squares algorithm for Wiener model identification of highly nonlinear systems

چکیده

Abstract

In this paper, an online identification algorithm is presented for nonlinear systems in the presence of output colored noise. The proposed method is based on extended recursive least squares (ERLS) algorithm, where the identified system is in polynomial Wiener form. To this end, an unknown intermediate signal is estimated by using an inner iterative algorithm. The iterative recursive algorithm adaptively modifies the vector of parameters of the presented Wiener model when the system parameters vary. In addition, to increase the robustness of the proposed method against variations, a robust RLS algorithm is applied to the model. Simulation results are provided to show the effectiveness of the proposed approach. Results confirm that the proposed method has fast convergence rate with robust characteristics, which increases the efficiency of the proposed model and identification approach. For instance, the FIT criterion will be achieved 92% in CSTR process where about 400 data is used.

Keywords: Iterative recursive algorithm Least squares identification Wiener model
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