Learning Feedforward Control of a One-Stage Refrigeration System

Refrigeration control is usually realized by means of model-based feedback controllers, which requires high-computational load and time-consuming model identification efforts. The implementation of feedback control requires a compromise between performance and robust stability. Considering these dif...

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Bibliographic Details
Main Authors: Yang Zhao, Yan Li, Sina Dehghan, YangQuan Chen
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8712485/
Description
Summary:Refrigeration control is usually realized by means of model-based feedback controllers, which requires high-computational load and time-consuming model identification efforts. The implementation of feedback control requires a compromise between performance and robust stability. Considering these difficulties, an online learning operation controller for one-stage refrigeration cycle is presented, which consists of two components: a model-based feedback component and a learning feedforward component. The feedback controller is utilized to guarantee robustness. Meanwhile, the optimized performance is reached by the learning feedforward controller including a one-hidden-layer structure with B-spline basis functions. The comparison results of benchmark problems validate the effectiveness of this strategy and show that a perfect tracking performance can still be achieved without extensive modeling.
ISSN:2169-3536