کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
695774 1460663 2015 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Data-driven model improvement for model-based control
ترجمه فارسی عنوان
بهبود مدل مبتنی بر مدل برای کنترل مبتنی بر مدل
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
چکیده انگلیسی

We present a framework for the gradual improvement of model-based controllers. The total time of the learning procedure is divided into a number of learning intervals. After a learning interval, the model is refined based on the measured data. This model is used to synthesize the controller that will be applied during the next learning interval. Excitation signals can be injected into the control loop during each of the learning intervals. On the one hand, the introduction of an excitation signal worsens the control performance during the current learning interval since it acts as a disturbance. On the other hand, the informative data generated owing to the excitation signal are used to refine the model using a closed-loop system identification technique. Therefore, the control performance for the next learning interval is expected to improve. In principle, our objective is to maximize the overall control performance taking the effect of the excitation signals explicitly into account. However, this is in general an intractable optimization problem. For this reason, a convex approximation of the original problem is derived using standard relaxations techniques for Experiment Design. The approximated problem can be solved efficiently using common optimization routines. The applicability of the method is demonstrated in a simulation study.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Automatica - Volume 52, February 2015, Pages 118–124
نویسندگان
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