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CONTROL OF A MAGNETIC FLYWHEEL BY A FUZZY NEURAL NETWORK ALGORITHM

机译:通过模糊神经网络算法控制磁性飞轮

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In this paper a magnetic flywheel system is studied with a magnetic bearing, which is able to support the shaft without mechanical contacts, and it is also able to control the rotational vibration. Magnetic flywheel system is composed of position sensors, a digital controller, actuating amplifiers, electromagnets and a flywheel. This work applies the fuzzy neural network (FNN) algorithm to control the vibration of a magnetic flywheel system. It proposes the design skill of an optimal controller when the system has the uncertainty, i.e. it has a difficulty in extracting the exact mathematical expressions. Two controllers are designed for the FNN in order to reduce the rotor vibration effectively. Unbalance response, which is a serious problem in rotating machineries, is improved by using a magnetic bearing with a FNN algorithm.
机译:在本文中,用磁轴承研究了磁性飞轮系统,该磁轴承能够在没有机械触点的情况下支撑轴,并且还能够控制旋转振动。磁性飞轮系统由位置传感器,数字控制器,致动放大器,电磁铁和飞轮组成。这项工作适用于控制磁飞轮系统的振动的模糊神经网络(FNN)算法。当系统具有不确定性时,它提出了最佳控制器的设计技巧,即,它难以提取确切的数学表达式。两个控制器设计用于FNN,以有效地减少转子振动。通过使用具有FNN算法的磁轴承,改善了旋转机械中的严重问题的不平衡反应。

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