کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4999754 | 1460632 | 2017 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Kernel-based identification of Wiener-Hammerstein system
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موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
کنترل و سیستم های مهندسی
پیش نمایش صفحه اول مقاله

چکیده انگلیسی
This paper addresses the problem of Wiener-Hammerstein (LNL) system identification. We present two estimates, which recover the static nonlinear characteristic and the linear dynamic blocks separately. Both algorithms are based on kernel preselection of data and application of local least squares and cross-correlation techniques. Formal proofs of consistency are derived under very mild a priori restrictions imposed on the input excitation and system characteristics. In particular, the input need not be Gausssian, and a wide (nonparametric) class of nonlinear characteristics is admitted. Finally, we propose a universal multi-stage identification strategy which allows to split the resulting linear model into two separate blocks. We also present a simple simulation example to illustrate the behavior of the method in practice.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Automatica - Volume 83, September 2017, Pages 275-281
Journal: Automatica - Volume 83, September 2017, Pages 275-281
نویسندگان
Grzegorz Mzyk, PaweÅ Wachel,