摘要
阳极焙烧燃油供给温度的精确控制是一个具有非线性特性的流体加热供给控制问题,实际测试表明,现有的PID控制很难实现对燃油供给温度的动态跟踪控制,影响燃油的充分喷射、雾化及其与空气的混合,使部分燃油得不到充分燃烧,造成了能源浪费和环境污染。提出基于粒子群优化模糊预测函数控制(PSO-F-PFC)的油料燃烧供给温度控制方法,通过与PID控制方法的比较,以及对阳极焙烧炉重油燃烧供给温度的动态跟踪控制表明,该方法优于原有燃油燃烧系统的PID控制,实现了燃油供给温度的动态跟踪精确控制。
The accurate control of fuel oil feeding temperature is a nonlinear dynamic tracking control problem.In practice,the fuel oil feeding temperature accurate dynamic tracking control is very difficult by traditional PID controller.It induces that it is very difficult to eject atomization and combine with air for fuel oil.So part of fuel oil have not get sufficient combustion.It always leads to waste of fuel oil and environmental pollution.These problems are solved by Fuzzy predictive functional control（F-PFC） for particle swarm optimization algorithm.These results of simulation and experiment show that the F-PFC has higher precision than the method of PID.It is proved that this method is effective in the fuel oil feeding temperature accurate dynamic tracking control for anode baking.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第9期200-203,共4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
阳极焙烧
燃油供给温度
粒子群优化辨识与优化
模糊预测函数控制(F-PFC)
anode baking
fuel oil feeding temperature
partical swarm optimization identification and optimization
Fuzzy predictivefunctional control
