کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5001743 1460975 2017 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multi-objective iterative learning control using convex optimization
ترجمه فارسی عنوان
کنترل یادگیری تکراری چند منظوره با استفاده از بهینه سازی محدب
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
چکیده انگلیسی
This paper presents a multi-objective iterative learning control (ILC) design approach that realizes an optimal trade-off between robust convergence, converged tracking performance, convergence speed, and input constraints. Linear time-invariant single-input single-output systems which are represented by both parametric and nonparametric models are considered. The noncausal filter Q(q) and learning function L(q) are simultaneously optimized by solving a convex optimization problem. The proposed method is applied to a non-minimal phase system and compared with a model-inversion based ILC design. Using the developed ILC design the underlying trade-off between tracking performance and convergence speed is thoroughly/quantitatively analyzed.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Control - Volume 33, January 2017, Pages 35-42
نویسندگان
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