摘要
针对铝合金在铸造的过程中铸造速度的不稳定性以及传统PID控制存在系统响应速度慢、超调量大等问题,设计出3个针对铸造速度控制的方案,并选择方案1作为速度控制方案,然后并对此方案的铸造速度控制各回路进行了设计与分析。利用模糊神经网络控制算法对PID 3个参数进行参数优化,并通过典型传递函数进行仿真实验,实验结果证明模糊神经网络控制算法能够有效地提升铸造速度控制的响应速度和控制精度,并具有良好的动态响应。
Aiming at the instability of casting speed of aluminium alloy in the process of casting and the problems of slow response speed and large overshoot in traditional PID control system. This paper designs three schemes for casting speed control, and chooses scheme 1 as the speed control scheme, then designs and analyses the various loops of casting speed control of this scheme. The three parameters of PID are optimized by using the fuzzy neural network control algorithm, and the simulation experiments are carried out through the typical transfer function. The experimental results show that the fuzzy neural network control algorithm can effectively improve the response speed and control accuracy of casting speed control, and has good dynamic response.
作者
田文龙
张寿明
Tian Wenlong;Zhang Shouming(Faculty of Information Engineering and Automation,Kunming University of Science and Technology Kunming,Yunnan Province 650000,china)
出处
《电子测量技术》
2019年第19期6-13,共8页
Electronic Measurement Technology