کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
494531 862799 2016 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A practical implementation of Robust Evolving Cloud-based Controller with normalized data space for heat-exchanger plant
ترجمه فارسی عنوان
اجرای عملیاتی از کنترلر مبتنی بر ابر در حال تکامل مقاوم با فضای داده نرمال شده برای نیروگاه مبدل حرارتی
کلمات کلیدی
سیستم در حال تکامل؛ کنترل تطبیقی مقاوم؛ سیستم مبتنی بر ابر فازی
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نرم افزارهای علوم کامپیوتر
چکیده انگلیسی


• An improved version of the Robust Evolving Cloud-based Controller (RECCo).
• Performance comparison with classical PID controller.
• Practical implementation and on-line control for real heat-exchanger plant.
• Evolving structure and adaptive law deal with the uncertainty of the system.
• Very basic information of the controlled process is required.

The RECCo control algorithm, presented in this article, is based on the fuzzy rule-based (FRB) system named ANYA which has non-parametric antecedent part. It starts with zero fuzzy rules (clouds) in the rule base and evolves its structure while performing the control of the plant. For the consequent part of RECCo PID-type controller is used and the parameters are adapted in an online manner. The RECCo does not require any off-line training or any type of model of the controlled process (e.g. differential equations). Moreover, in this article we propose a normalization of the cloud (data) space and an improved adaptation law of the controller. Due to the normalization some of the evolving parameters can be fixed while the new adaptation law improves the performance of the controller in the starting phase of the process control. To assess the performance of the RECCo algorithm, firstly a comparison study with classical PID controller was performed on a model of a plate heat-exchanger (PHE). Tuning the PID parameters was done using three different techniques (Ziegler–Nichols, Cohen–Coon and pole placement). Furthermore, a practical implementation of the RECCo controller for a real PHE plant is presented. The PHE system has nonlinear static characteristic and a time delay. Additionally, the real sensor's and actuator's limitations represent a serious problem from the control point of view. Besides this, the RECCo control algorithm autonomously learns and evolves the structure and adapts its parameters in an online unsupervised manner.

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ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Soft Computing - Volume 48, November 2016, Pages 29–38
نویسندگان
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