神经网络控制在电厂锅炉中的应用

Jianyong Li, E. Ososanya, R. A. Smoak
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引用次数: 1

摘要

两种神经网络分别用于电厂锅炉节流压力和兆瓦负荷的控制,其中一种网络作为仿真器,另一种网络作为控制器。学习方案是一个两阶段的过程,其中第一阶段包括训练模拟器映射植物动力学,第二阶段包括训练控制器网络使用反向传播算法学习期望的性能并最小化植物输出误差代价函数。该实例说明了神经网络技术在电厂控制领域的潜在应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The neural network control application in a power plant boiler
Two neural networks are used in the control of power plant boiler throttle pressure and megawatt load, where one network acts as an emulator, and the other as a controller. The learning scheme is a two-phase procedure in which the first involves training the emulator in mapping the plant dynamics and the second to train a controller network to learn the desired performance using a backpropagation algorithm and minimize plant output error cost function. This example illustrates the potential application of neural network technique in the power plant control area.
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