混合式熔炼保温压铸炉温度控制优化研究

Study on Temperature Control and Optimization of Mixed Melting Heat Preservation Die-casting Furnace

为了降低温度控制误差和随机扰动对温度影响,提出了混合式熔炼保温压铸炉温度控制优化方法。结合PID控制器与模糊神经网络,设计模糊神经网络PID控制器,通过两输入一输出的模糊神经网络结构,解决PID参数在线整定困难问题;通过寻找最佳网络结构和参数,以遗传算法为基础,采用离线优化算法,通过初始化参数、网络结构学习以及参数优化三个步骤优化模糊神经网络控制器,实现混合式熔炼保温压铸炉最佳温度控制优化。经实验验证:该方法温度变化波动与温度误差较小,且加入固定扰动和随机扰动时温度变化小。

In order to reduce the influence of temperature control error and random disturbance on temperature,an optimization method for temperature control of hybrid smelting holding die casting furnace was proposed.Combined with PID controller and fuzzy neural network,the fuzzy neural network PID controller is designed.Through the fuzzy neural network structure of two inputs and one output,the problem of PID parameters online tuning is solved.By finding the best network structure and parameters,based on genetic algorithm,the off-line optimization algorithm is adopted,and the PID parameters are optimized through three steps:initialization parameters,network structure learning and parameter optimization The fuzzy neural network controller is used to optimize the optimal temperature control of the hybrid smelting holding die casting furnace.The experimental results show that the temperature fluctuation and temperature error of this method are small,and the temperature change is small when the fixed disturbance and random disturbance are added..