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Application of neural network based fuzzy control to power system generator

机译:神经网络模糊控制在电力系统发生器中的应用

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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.
机译:作者介绍了使用神经网络理论的电力系统中的模糊控制在电力系统中的应用。在该方法中,通过使用神经网络的学习过程来确定隶属函数。对于模糊规则的RHS(右侧),他们建议使用最佳控制,使得即使系统在除线性化点的某些其他工作点处运行时也可以控制系统。机器电源输出被认为是操作点的变化。尽管使用所提出的方法的控制与线性化点使用最佳控制方法的控制不那么好,但是可以通过更广泛的范围控制电力系统而不是最佳控制方法。

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