温度控制系统时滞对象的先进PID控制方法研究  

Study on advanced PID control method of temperature control system delay object

作　　者：郑英杰 牛兴华 高卫国[2] 刘腾[3] ZHENG Ying-jie;NIU Xing-hua;GAO Wei-guo;LIU Teng(School of Mechanical Engineering, Tianjin Key Laboratory of the Design and Intelligent Control of the Advanced Mechatronical System, Tianjin University of Technology, Tianjin 300384, China;School of Mechanical Engineering, Key Laboratory of Mechanism Theory and Equipment Design （Tianjin University）, Ministry of Education, Tianjin University, Tianjin 300354, China;School of Mechanical Engineering, Hebei University of Technology, Tianiin 300130, China)

机构地区：[1]天津理工大学机械工程学院天津市先进机电系统设计与智能控制重点实验室,天津300384 [2]天津大学机械工程学院教育部机构理论与装备设计重点实验室,天津300354 [3]河北工业大学机械工程学院,天津300130

出　　处：《天津理工大学学报》2018年第4期20-25,共6页Journal of Tianjin University of Technology

基　　金：国家自然科学基金(51775375);天津市科技重大专项项目(2016ZX04004-002);河北省自然科学基金青年项目(E2017202194);河北省普通高等学校青年拔尖人才计划项目(BJ2017039)

摘　　要：滞后问题在工业过程控制中普遍存在,为使温控系统时滞控制获得较好的控制效果,选取反向传播(Back Propagation,BP)神经网络和径向基(Radial Basis Function,RBF)神经网络两种先进PID控制算法整定控制参数.运用Matlab软件对控制算法进行仿真并对比分析算法的控制效果,为系统控制算法选取及模块开发提供参考.Lag problem is common in industrial process control. To make the time-delay control of temperature control system achieve good control effect, selecting Back Propagation neural network and Radial Basis Function neural network which are two kinds of advanced algorithm to adjust the control parameters of PID control. For providing a reference for the control algorithm selection and module development, using the Matlab software to simulate the control algorithm and analyzing the control effect.

关 键 词：控制系统 滞后 PID控制 BP神经网络 RBF神经网络 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]