基于ARM的嵌入式自适应温度控制系统设计  

Design of embedded adaptive temperature control system based on ARM

作　　者：刘尘尘 LIU Chen-chen(School of Information Technology, Xichang University, Xichang 615013, China)

机构地区：[1]西昌学院信息技术学院,四川西昌615013

出　　处：《沈阳工业大学学报》2020年第4期448-452,共5页Journal of Shenyang University of Technology

基　　金：四川省教育厅自然科学青年基金项目(11ZB115)。

摘　　要：针对传统电阻炉温控系统受时滞长、惯性大和非线性等因素影响而普遍存在超调量大和调节时间长等问题,设计了一种基于ARM的嵌入式自适应温度控制系统.采用基于神经网络的PID自适应控制器对温度进行准确控制,提出了模糊Smith预估补偿控制方法来消除纯滞后系统的超调并提高稳定性,并将该方法与传统PID和模糊PID的控制方法进行了比较.结果表明,该系统能够实现电阻炉温度的快速和准确控制.相对于其他两种方法,该方法在系统超调和调节时间方面有极大提高,增强了系统的鲁棒性,具有较好的工程应用前景.In order to solve the problems of large overshoot and long adjustment time existing in the traditional resistance furnace temperature control system,which is affected by long time delay,large inertia and non-linearity,an embedded adptive temperature control system based on ARM was designed.A PID adaptive controller based on neural network was used to accurately control the temperature.Furthermore,a fuzzy Smith predictive compensation control method was proposed to eliminate the overshoot and improve the stability of pure time delay system.The as-proposed method was compared with traditional PID control and fuzzy PID control methods,respectively.The results show that the designed system can achieve fast and accurate temperature control of resistance furnace.Compared with the other two methods,the as-proposed method greatly improves the system overshoot and adjustment time,and enhances the system robustness,showing a good prospects for engineering application.

关 键 词：温度控制 电阻炉 神经网络 PID自适应控制 模糊Smith 预估补偿 鲁棒性 

分 类 号：TN248.4[电子电信—物理电子学]