燃油温度的多变量模糊预测函数控制  

Dynamic Tracking Multi-variable Fuzzy Predictive Functional Control of Fuel Oil Feeding Temperature

作　　者：李晓斌[1] 孙海燕[1] 吴燕翔[1] 寇得民[2] 李袆琛 

机构地区：[1]上海海洋大学工程学院,上海200091 [2]兰州理工大学电气与信息工程学院,甘肃兰州730050

出　　处：《工业加热》2008年第4期27-32,共6页Industrial Heating

基　　金：国家科技攻关计划资助项目(2002BA901A28);上海海洋大学博士科研基金资助项目(A-3605-08-0224)

摘　　要：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多变量控制问题,实际测试表明,现有的单回路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。基于粒子群优化模糊预测函数控制(PSO-F-MPFC)的油料燃烧供给温度多变量解耦控制方法,通过与PID控制方法的比较,以及在阳极焙烧炉重油燃烧供给温度的动态跟踪控制应用表明,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 multi-variable control problem. In practice, the fuel oil feeding temperature accurate dynamic tracking control is very difficult by traditional PID controller. It induced that it is very difficult to ejected atomization and combine with air for fuel oil. So part of fuel oil had not get sufficient combustion. It always leads to waste of fuel oil and environmental pollution. These problems are solved by Fuzzy predictive functional multi-variable control （F-MPFC） for particle swarm optimization algorithm. These results of simulation and experiment know that the F-MPFC 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.

关 键 词：阳极焙烧 燃油供给温度 PSO辨识与优化 模糊预测函数多变量控制(F-MPFC) 

分 类 号：TF806.1[冶金工程—有色金属冶金] TP273[自动化与计算机技术—检测技术与自动化装置]