摘要
在纤维、造纸、塑料及金属镀膜工业中 ,对线状、带状及面状弹性材料卷取张力的控制是关系其产品质量的关键技术。介绍了一种带有反向传播训练算法的人工神经网络 ,该方法克服了传统 PI控制方法的缺点 ,有效地减弱了张力控制系统中速度和张力之间的耦合作用。仿真结果表明该种控制方法有良好效果。
Within the field of fiber, paper making, plastic and metal plating, one of the key techniques to guarantee the product quality is for the control of winding tension of linear, strip and area materials. In this paper, the authors introduced a kind of artificial neural network with back-propagation training algorithm. This method overcame the shortcomings of the traditional PI control method, and effectively weakened the coupling action between the velocity and tension of the tension control system. Some simulation results indicated the favorable effect of the control algorithm.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2001年第8期873-875,共3页
China Mechanical Engineering
关键词
纤维缠绕
张力控制系统
神经网络
耦合
filament winding tension control neural network coupling
