汽轮发电机组神经网络模型和控制器的在线训练

Proceedings of the First International Forum on Applications of Neural Networks to Power Systems Pub Date : 1991-07-23 DOI:10.1109/ANN.1991.213515

Qinghua Wu, B. Hogg, George W. Irwin

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引用次数: 4

摘要

研究了一种用于汽轮发电机组自适应控制的神经网络调节器。神经网络调节器是基于神经网络的层次结构设计的。在神经网络调节器中分层使用BP算法对汽轮发电机神经网络模型和控制器进行在线训练。利用多层神经网络对汽轮发电机组系统进行了动态建模研究。将神经网络调节器应用于一个复杂非线性汽轮发电机系统的仿真中。给出了在不同运行条件和干扰下神经网络调节器性能的仿真结果。

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On-line training of neural network model and controller for turbogenerators

The authors are concerned with the development of a neural network (NN) regulator for turbogenerator adaptive control. The NN regulator is designed based on a hierarchical architecture of neural networks. The back-propagation (BP) algorithm is used hierarchically in the NN regulator for on-line training of the turbogenerator NN model and controller. Dynamic modelling of the turbogenerator system has been investigated using the multilayer NN. The NN regulator has been implemented on a simulated complex nonlinear turbogenerator system. Simulation results evaluating the performance of the NN regulator under different operation conditions and disturbances are presented.<>

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Proceedings of the First International Forum on Applications of Neural Networks to Power Systems

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