Adaptive control system for continuous steel casting based on neural networks and fuzzy logic

被引：23

作者：

Tirian, Gelu-Ovidiu ^{[1
]}

Filip, Ioan ^{[2
]}

Prostean, Gabriela ^{[3
]}

机构：

[1] Politehn Univ Timisoara, Dept Elect Engn & Comp Ind, Fac Engn, Hunedoara, Romania

[2] Politehn Univ Timisoara, Dept Automat & Appl Informat, Fac Automat & Comp Sci, Hunedoara, Romania

[3] Politehn Univ Timisoara, Dept Management, Fac Management Prod & Transport, Hunedoara, Romania

来源：

NEUROCOMPUTING | 2014年 / 125卷

关键词：

Neural networks; Fuzzy logic; Continuous casting; Cracks; Adaptive control system; MOLD;

D O I：

10.1016/j.neucom.2012.11.052

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The present paper describes a neural network-based strategy for crack prediction aimed at improving the steel-casting process performance by decreasing the number of crack-generated failure cases. A neural system to estimate crack detection probability has been designed, implemented, tested and integrated into an adaptive control system. The neural system, consisting of two distinct neural networks, provides 0 or 1 probability values (1-high probability of crack occurrence, 0-low probability of crack occurrence). Also, a decision block, based on fuzzy logic (implementing an expert system), has been designed and implemented, triggering one or the other specific set of rules (according to 0 or 1 value of neural system) and tuning the set point of the control system. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：236 / 245

页数：10

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