کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4976940 | 1451841 | 2017 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Incomplete data based parameter identification of nonlinear and time-variant oscillators with fractional derivative elements
ترجمه فارسی عنوان
شناسایی پارامترهای ناقص داده شده از نوسانگرهای غیر خطی و زمان با عناصر مشتق شده کسری
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کلمات کلیدی
شناسایی سیستم، سیستم غیرخطی مشتق مکرر، موجک هارمونی، داده های ناقص،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
پردازش سیگنال
چکیده انگلیسی
Various system identification techniques exist in the literature that can handle non-stationary measured time-histories, or cases of incomplete data, or address systems following a fractional calculus modeling. However, there are not many (if any) techniques that can address all three aforementioned challenges simultaneously in a consistent manner. In this paper, a novel multiple-input/single-output (MISO) system identification technique is developed for parameter identification of nonlinear and time-variant oscillators with fractional derivative terms subject to incomplete non-stationary data. The technique utilizes a representation of the nonlinear restoring forces as a set of parallel linear sub-systems. In this regard, the oscillator is transformed into an equivalent MISO system in the wavelet domain. Next, a recently developed L1-norm minimization procedure based on compressive sensing theory is applied for determining the wavelet coefficients of the available incomplete non-stationary input-output (excitation-response) data. Finally, these wavelet coefficients are utilized to determine appropriately defined time- and frequency-dependent wavelet based frequency response functions and related oscillator parameters. Several linear and nonlinear time-variant systems with fractional derivative elements are used as numerical examples to demonstrate the reliability of the technique even in cases of noise corrupted and incomplete data.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechanical Systems and Signal Processing - Volume 94, 15 September 2017, Pages 279-296
Journal: Mechanical Systems and Signal Processing - Volume 94, 15 September 2017, Pages 279-296
نویسندگان
Ioannis A. Kougioumtzoglou, Ketson R.M. dos Santos, Liam Comerford,