摘要
对铸坯冷却过程模型进行了改进,同时采用最小方差自适应控制策略和多层前馈神经网络技术,设计了一种铸坯表面温度自适应控制器,该方法克服了传统的拉速配水和根据传热学模型控制喷水的不足,具有一定的实用价值.
A new model describing slab solidification procedure is presented. On the basis of this model, a least mean square (LMS) adaptive control strategy is developed and realized by using two multi-layer neural networks. It can eliminate the inaccurate and uneven temperature distribution over the slab, which is usual in continuous casting with traditional cooling control systems.
出处
《甘肃工业大学学报》
北大核心
2002年第1期62-64,共3页
Journal of Gansu University of Technology
基金
国家自然科学基金(69635010)
