PID神经网络算法对K型热电偶非线性校正Nonlinear correction of K-type thermocouple using PID neural network algorithm
苏淑靖,吕楠楠,翟成瑞
摘要(Abstract)：
针对火箭发射场发射效应测温系统中K型热电偶存在的非线性特性,设计中将非线性特殊点作为训练样本,采用新型动态PID神经网络算法对热电偶进行非线性校正。针对基本BP算法收敛慢、易陷入局部极值的缺点,提出利用粒子群算法来改进网络的寻优过程,并在传统算法基础上对其惯性权值的递减式子进行改进。使用Matlab建模仿真表明,改进算法在寻优过程中,收敛速度快,全局寻优能力强,有较好的控制效果。拟合出的温度电压关系呈现好的线性度,相对误差均控制在1%以内,提高了系统测试精度,满足对火箭发射时温度环境效应的监测要求。
关键词(KeyWords)： PID神经网算法;K型热电偶;粒子群优化;非线性校正;惯性权值;Matlab
基金项目(Foundation): 国家自然科学基金(51675493)~~
作者(Author): 苏淑靖,吕楠楠,翟成瑞
DOI: 10.16652/j.issn.1004-373x.2018.14.019
参考文献(References)：
- [1]段艳明.基于PSO算法和BP神经网络的PID控制研究[J].计算机技术与发展,2014,24(8):238-241.DUAN Yanming.Reserch of PID control based on BP neural network and PSO algorithm[J].Computer technology and development,2014,24(8):238-241.
- [2]朴海国,王志新.基于CPSO的PID神经网络及偏航电机控制策略[J].电机与控制学报,2010,14(9):55-62.PIAO Haiguo,WANG Zhixin.Control strategy of CPSO-based PID neural network and a yaw motor[J].Electric machines and control,2010,14(9):55-62.
- [3]GAO M Y,CHEN S X,CHENG L L,et al.Online measurement of battery internal resistance based on AC impedance method[J].Advanced materials research,2013,718-720:773-778.
- [4]屈毅,宁铎,赖展翅,等.温室温度控制系统的神经网络PID控制[J].农业工程学报,2011,27(2):307-311.QU Yi,NING Duo,LAI Zhanchi,et al.Neural networks based on PID control for greenhouse temperature[J].Transactions of the Chinese Society of Agricultural Engineering,2011,27(2):307-311.
- [5]于立君,陈佳,刘繁明,等.改进粒子群算法的PID神经网络解耦控制[J].智能系统学报,2015,10(5):699-704.YU Lijun,CHEN Jia,LIU Fanming,et al.An improved particle swarm optimization for PID neural network decoupling control[J].CAAI transactions on intelligent systems,2015,10(5):699-704.
- [6]MOHANDES M A.Modeling global solar radiation using particle swarm optimization[J].Solar energy,2012,86(11):3137-3145.
- [7]沈锡.基于粒子群优化算法的船舶航向PID控制[D].大连:大连海事大学,2011.SHEN Xi.Ship course PID control based on particle swarm optimization[D].Dalian:Dalian Maritime University,2011.
- [8]周西峰,林莹莹,郭前岗.基于粒子群算法的PID神经网络解耦控制[J].计算机技术与发展,2013,23(9):158-161.ZHOU Xifeng,LIN Yingying,GUO Qiangang.PID neural network decoupling control based on particle swarm optimization[J].Computer technology and development,2013,23(9):158-161.
- [9]应进.基于粒子群算法的航空发动机多变量控制研究[D].南昌:南昌航空大学,2011.YING Jin.Research on multi-variable control of aero engine based on particle swarm optimization[D].Nanchang:Nanchang Hangkong University,2011.
- [10]俞凯耀,席东民.人工鱼群算法优化的PID神经网络解耦控制[J].计算机仿真,2014,31(10):350-353.YU Kaiyao,Xi Dongmin.Optimized PID neural network decoupling control based on artificial fish optimization[J].Computer simulation,2014,31(10):350-353.