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Defuzzification filters and applications to power system stabilization problems

机译:除模糊滤波器及其在电力系统稳定问题中的应用

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Defuzzification is a very important step in fuzzy systems applications. There are a number of different defuzzification methods reported in the literature. In this paper, the concept of defuzzification filters in a control system setting is first discussed and a methodology for designing such filters considered. As will be seen, the design of such filters requires the knowledge of the plant model and its inverse. A reference control signal is computed and then is used to generate the actual defuzzified control signal which will be applied to control the plant. The application of the defuzzification filter is made by introducing the filter into a power system in which a neuro-fuzzy self-learning controller was applied to stabilize the system but success could not always be guaranteed. With the defuzzification filter, however, the system is always stabilized. Simulation results are presented. (C) 2000 Academic Press. [References: 33]
机译:模糊化是模糊系统应用中非常重要的一步。文献中报道了许多不同的去模糊方法。在本文中,首先讨论了控制系统设置中的去模糊滤波器的概念,并考虑了设计此类滤波器的方法。可以看到,这种滤波器的设计需要了解工厂模型及其逆模型。计算参考控制信号,然后将其用于生成实际的去模糊控制信号,该信号将用于控制工厂。去模糊滤波器的应用是通过将滤波器引入电力系统来实现的,在该电力系统中,应用了神经模糊自学习控制器来稳定系统,但是不能总是保证成功。但是,使用去模糊滤波器,系统始终稳定。给出了仿真结果。 (C)2000学术出版社。 [参考:33]

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