摘要
为了解传统加热炉炉温控制存在的大滞后、温度调控精度较差等问题,采用分阶段的方式建立加热炉炉温控制系统模型,该模型主要在BP神经网络机制和PID算法的基础上完成构建。利用STM32F103单片机作为硬件系统的核心设备。为最大限度地提升PID算法效能,对传统PID算法进行改进。为验证加热炉炉温控制系统硬件和软件方案的合理性,对加热炉炉温控制系统的调控器进行测试。测试结果表明,该调控器在实际工作过程中具有良好的稳定性,可满足加热炉炉温控制系统对精准度的需求。
In order to understand the problems of traditional heating furnace temperature control,such as big lag and poor temperature control accuracy,the heating furnace temperature control system model is established by stages.The model is mainly built on the basis of BP neural network mechanism and PID algorithm.STM32 F103 MCU is used as the core equipment of the hardware system.In order to maximize the efficiency of PID algorithm,the traditional PID algorithm is improved.In order to verify the rationality of the hardware and software of the heating furnace temperature control system,the governor of the heating furnace temperature control system was tested.The test results show that the controller has good stability in the actual working process,and can meet the demand for precision of heating furnace temperature control system.
作者
傅峰
FU Feng(Information technology branch of Xinjiang Agricultural Vocational and Technical College,Changji 831100,China)
出处
《工业加热》
CAS
2022年第10期27-30,共4页
Industrial Heating
基金
职业教育信息安全与管理专业资源库课程建设基金(2016-B02)。
关键词
模糊PID控制
改进PID算法
加热炉
炉温控制系统
fuzzy PID control
improved PID algorithm
heating furnace
furnace temperature control system
作者简介
傅峰(1978-),男,硕士,副教授,研究方向为物联网、信息安全.
