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文中介绍了基于BP(BackPropagation)的神经网络气化炉温度控制系统。对BP神经网络控制算法作了详细的介绍,运用模糊逻辑控制概念赋予隐层含义,并决定其节点数,同时用高斯核函数作为节点激励函数,并做了仿真研究,叙述了系统的硬件与软件构成,试验表明所设计的系统操作方便、安全可靠,所选择的控制算法适应性强,控制效果良好。
This paper introduces BP neural network gasifier temperature control system based on BP (BackPropagation). The control algorithm of BP neural network is introduced in detail. The concept of hidden layer is given by the concept of fuzzy logic control, and the number of nodes is determined. At the same time, the Gaussian kernel function is used as the excitation function of the node, and the simulation study is carried out. The system hardware and Software composition, the test shows that the designed system is easy to operate, safe and reliable. The selected control algorithm has strong adaptability and good control effect.