Application of neural network based fuzzy control to power system generator

Proceedings of the First International Forum on Applications of Neural Networks to Power Systems Pub Date : 1991-07-23 DOI:10.1109/ANN.1991.213485

K. Saitoh, S. Iwamoto

引用次数: 3

Abstract

The authors present an application of fuzzy control to a synchronous machine in a power system using the neural network theory. In this method, the membership function is determined by using the learning process of the neural network. For the RHS (right hand side) of fuzzy rules, they propose to use the optimal controls so that they can control the system even if the system is operated at some other operating points than the linearized point. The machine power output is considered as the change of operating points. Although the control using the proposed method is not so good as the control using the optimal control method at the linearized point, one can control the power system by the proposed method at wider ranges than the optimal control method.<>

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基于神经网络的模糊控制在电力系统发电机中的应用

提出了一种基于神经网络理论的模糊控制在电力系统同步电机中的应用。该方法利用神经网络的学习过程确定隶属度函数。对于模糊规则的RHS(右侧)，他们提出使用最优控制，以便即使系统在线性化点以外的其他工作点运行，他们也可以控制系统。将机器输出功率视为工作点的变化。虽然在线性化点处的控制效果不如最优控制，但在较宽的范围内可以实现对电力系统的控制。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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