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
收藏
页码：236 / 245
页数：10
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