Application research on foam glass kiln temperature control model and strategy

被引：0
作者：
Du, X.J. [1 ]
Shi, S.T. [2 ]
机构：
[1] College of Electrical and Information Engineering, Lanzhou University of Technology
[2] China Energy Engineering Group Co. Ltd.
来源：
Information Technology Journal | 2013年 / 12卷 / 23期
关键词：
Clonal Selection Algorithm (CSA); Foam glass; Kiln; Optimized Fuzzy Neural Network (OFNN); Temperature control;
D O I：
10.3923/itj.2013.7803.7808
中图分类号：
学科分类号：
摘要：
Foam glass production process is a typical nonlinear, large time delay, large inertia, strong cross-coupling, time-varying and complex control object. In this study, a new temperature control strategy is proposed by analyzing the working mechanism of the kiln and the temperature control problem in it. In the application, the Optimized Fuzzy Neural Network (OFNN) is applied to model the foam glass kiln and its weights and threshold value of the neural network are optimized by the Clonal Selection Algorithm (CSA) of the immune system theory. The structure of the controller is modified at any time in the process of production according to the temperature output error and its aim is to achieve the most stable temperature control of the foam glass production process in the kilns. The application of the model in the control system is successful and effective to improve the glass product quality. © 2013 Asian Network for Scientific Information.
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页码：7803 / 7808
页数：5
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