流化床锅炉燃烧系统的神经网络解耦控制

Neural network decoupling control strategy and its applications in combustion system of fluidized bed boiler

提出了一种基于BP算法的人工神经网络解耦控制策略,并将其应用于流化床锅炉的燃烧系统中,其思想是在加入神经网络解耦环节以后,使得包括该解耦环节在内的广义被控对象的第一系数矩阵为对角矩阵。仿真结果证明,该策略能收到良好的控制效果,成功解决了主汽压力和料床温度的燃烧系统控制难题:即同时控制给煤量和一次送风量,有望用于循环流化床锅炉燃烧系统这类复杂过程的控制。

A neural network decoupling control strategy based on BP arithmetic is presented,which is applied in the combustion system of fluidized bed boiler.The idea is to make the prima -ry coefficient matrix of the broad controlled object including the decoupling unit a diagonal matrix.With its help,the com bustion system control of main steam pressure and bed temperature is successfully achieved.The simulation re sult shows that the coal supply and the primary air supply are controlled at the same time.This strategy can be used in complicated process con trol as in the combustion sys-tem control of circulating fluidized bed boiler.