摘要
目的提高注塑机料筒温度控制的精度和稳定性,解决注塑机多段温度控制系统存在的非线性、强耦合、时变性等问题。方法通过分析注塑机的结构及工作原理,利用基于神经网络的静态解耦策略,将相互耦合的回路解耦成单回路系统,并采用粒子群算法优化模糊PID的量化因子。结果仿真及测试表明,各料筒温度响应较迅速,料筒温度超调小,稳态控制误差小,能够获得良好的控制效果。结论通过仿真显示,该控制策略能够克服料筒各段之间的耦合影响,适应性强,稳定性好,有一定的抗干扰能力,使注塑机的温度控制效果得到明显改善,具有一定的实用价值。
The work aims to improve the accuracy and stability of the temperature control of the injection molding machine barrel, and solve such problems as nonlinearity, strong coupling and time variation in the multi-stage temperature control system of the injection molding machine. By analyzing the structure and working principle of the injection molding machine, the intercoupled circuits were decoupled as a single-circuit system with the static decoupling strategy based on the neural network; and the quantization factor of fuzzy PID was optimized by particle swarm optimization. The simulation and test showed that, the temperature response of each barrel was relatively fast, the barrel temperature overshoot was small, and the homeostatic control error was small, so that good control effects could be achieved. The simulation shows that, the proposed control strategy can overcome the coupling effects occurring between sections of the barrel. With strong adaptation, good stability and certain capacity of resisting disturbance, the temperature control effects of the injection modeling machine can be significantly improved, which has certain practical value.
作者
李明辉
张孝杰
LI Ming-hui ZHANG Xiao-jie(Xijing University, Xi＇an 710021, China Tap Water Company of Puyang City, Puyang 457000, China)
出处
《包装工程》
CAS
北大核心
2017年第19期179-184,共6页
Packaging Engineering
关键词
料筒温度
静态解耦
自适应控制
barrel temperature
static decoupling
adaptive control
