摘要
针对油料加热输送过程中具有大时滞非线性特点的流动加热控制问题,提出了一种智能预测控制方法。该方法采用自适应粒子群优化算法(APSO)辨识和优化预测模型及控制器的PID控制参数,克服油料流动加热控制模型的失配及系统的不确定性。通过对已知模型的仿真,以及与自整定PID控制的比较表明,该方法具有较好的控制效果。
In order to solve the control problem with large time delay and uncertainty concerning fluid heating in the process of heavy oil transfer.An intelligent predicting variable parameters PID control method based on the predictive model is suggested.This method adopts Adaptive Particle Swarm Optimization(APSO) to solve unmatched model,the variable parameters to overcome the system uncertainty,and APSO to identify the model parameters and to optimize the PID control parameters of the controller.The simulation and application results show that the method is better than self-tuning PID.It has hopeful application prospect.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第2期197-200,208,共5页
Computer Engineering and Applications
基金
国家科技攻关计划项目No.2002BA901A28
上海海洋大学博士科研启动基金(No.A-3605-08-0224)~~
关键词
油料
输送温度
智能预测
自适应粒子群优化算法
变参数PID
控制方法
oil
heating flow temperature
intelligent predicting
Adaptive Particle Swarm Optimization (APSO)
variable parameters PID
control method