基于神经网络PID算法的镀液温度控制系统  

Bath Temperature Control System Based on Neural Network PID

作　　者：雷翔霄[1,2] 徐立娟[1] 唐春霞[1] LEI Xiangxiao;XU Lijuan;TANG Chunxia(Changsha Social Work College,Changsha 410004,China;College of Electrical and Informa-tion Engineering,Hunan University,Changsha 410082,China)

机构地区：[1]长沙民政职业技术学院,湖南长沙410004 [2]湖南大学电气与信息工程学院,湖南长沙410082

出　　处：《电镀与精饰》2020年第8期39-42,共4页Plating & Finishing

基　　金：湖南省自然科学基金(2019JJ70005);湖南省职业院校教育教学改革研究项目(ZJGB2019002);国家自然科学基金(51677063)。

摘　　要：设计了电镀槽液的温度控制系统,采用BP神经网络改进PID算法,实现了获得近似最优控制参数,并将BP-PID算法应用于电镀槽液温控系统中。在MATLAB中仿真实验表明,BP-PID控制算法能快速的整定出最优PID参数,并使系统达到较好的控制效果。实际应用表明:当控制温度为60℃时,BP-PID算法与常规PID算法相比具有更好的控温效果,超调率小于3%,稳态精度小于±1.5℃。A temperature control system of electroplating solution was designed.BP neural network was used to improve the PID algorithm to achieve the approximate optimal control parameters,and the BPPID algorithm was applied to the solution temperature control system.The simulation experiment in MATLAB showed that the BP-PID algorithm could adjust the optimal PID parameters quickly,and make the system achieve a preferable control effect.The practical application showed that the BP-PID algorithm had better temperature control effect than the conventional PID algorithm when the temperature was 60℃.The overshoot rate was less than 4%,and the steady-state accuracy was less than 1.5℃.

关 键 词：电镀 BP神经网络 PID算法 BP-PID算法 

分 类 号：TP278[自动化与计算机技术—检测技术与自动化装置]