基于MyPSO-BP的黄酒发酵温控系统  

Rice Wine Fermentation Temperature Control System Based on MyPSO-BP

作　　者：赵兢兢[1] 刘柱[1] 许文强[1] 徐保国[1] 

机构地区：[1]江南大学物联网工程学院,江苏无锡214122

出　　处：《计算机工程》2012年第7期247-249,共3页Computer Engineering

基　　金：国家"863"计划基金资助项目(2007AA10Z241;2006AA10A301);国家部委基金资助项目;江苏省博士后基金资助项目(1101021B)

摘　　要：在Labview组态软件、西门子PLC300和温度传感器构成的温度控制系统基础上,提出一种新的黄酒发酵温度控制系统,将带交叉因子的粒子群优化(PSO)算法应用到BP神经网络(MyPSO-BP)比例积分微分(PID)控制中。改进的PSO算法初始化神经网络的权重和阈值,可以更好地在线整定PID参数,增强系统的稳定性和鲁棒性,减小误差。对系统进行Matlab仿真实验,结果表明,该系统相较于传统的神经网络PID控制器具有更好的温度控制性能。A novel temperature control method for rice wine fermentation control system is proposed,based on the system consisting of Labview,SIMATIC PLC300 and sensors.In this algorithm,cross-factor Particle Swarm Optimization（PSO） is applied to the BP neural network（MyPSO-BP） Proportion-Integral-Differential（PID） control.The improved particle swarm algorithm initializes the weights and thresholds of neural network,which can be an effective approach to tuning PID parameters on-line,enhancing system stability and robustness and reducing errors.Simulation experiment is performed by Matlab,and simulation result shows that this method compared with the traditional neural network PID controller has a great advantage in temperature control performance.

关 键 词：黄酒发酵温控 BP神经网络 粒子群优化 比例积分微分控制 交叉因子 惯性权重 

分 类 号：TP334.4[自动化与计算机技术—计算机系统结构]