کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7104158 1460335 2018 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A Finite Horizon Markov Decision Process Based Reinforcement Learning Control of a Rapid Thermal Processing system
ترجمه فارسی عنوان
یک فرآیند تصمیم گیری مارکف متشکل از تقویت کننده کنترل یک سیستم پردازش سریع سیستم حرارتی
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی تکنولوژی و شیمی فرآیندی
چکیده انگلیسی
Manufacture of ultra large-scale integrated circuits involves accurate control of a challenging nonlinear Rapid Thermal Processing (RTP) system. Precise control of temperature profile and rapid ramp-up and ramp-down rates demanded by a RTP system cannot be achieved with conventional control strategies due to nonlinear and multi time-scale effects. In this paper the control of a RTP system is reformulated as an optimal multi-step sequential decision problem using the framework of finite horizon Markov decision processes and solved using a Reinforcement Learning (RL) algorithm. Three increasingly complex RL based control strategies are explored and compared with the existing state-of-the-art approach for controlling RTPs. Simulation results indicate that the approach proposed in this paper achieves superior control of the temperature profile and ramp-up and ramp-down rates for the RTP system.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Process Control - Volume 68, August 2018, Pages 218-225
نویسندگان
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