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CONTROL OF SHAFT VIBRATIONS ON MAGNETIC BEARINGS USING NEURAL NETWORK AND SLIDING MODE CONTROLLER

机译:使用神经网络和滑模控制器控制磁轴承上的轴振动

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摘要

This article discusses a method for complete control of the dynamics of a rotating shaft on magnetic bearings under the effects of mass imbalance. The electromagnetic bearings used in this research are 2 four-pole bearing at the two ends of the rotor, which are actuated by differential currents. Full dynamic behavior of 3- dimensional rigid rotor and its effects on dynamic model are included. The effects of rotating mass unbalance are also included in the equations. The geometric couplings between electromagnetic forces of the coils are included as uncertainty. By using sliding mode controller and a neural network to estimate the system nonlinear-coupled equations, in a way suitable for sliding mode controller, a controller for this 4 input system is designed. Using a computer simulation of the real system, the difference between actual and estimated model and the effects of the controller are studied. For different operating modes the controller parameters are then determined. The present method allows the controller to apply necessary changes required by the time variant system equations.
机译:本文讨论了一种在质量不平衡的影响下完全控制磁性轴承上旋转轴动力学的方法。这项研究中使用的电磁轴承是转子两端的2个四极轴承,由差动电流驱动。包括3维刚性转子的全动态行为及其对动力学模型的影响。旋转质量不平衡的影响也包括在公式中。线圈电磁力之间的几何耦合作为不确定性包括在内。通过使用滑模控制器和神经网络来估计系统非线性耦合方程,以适合滑模控制器的方式,设计了该4输入系统的控制器。使用真实系统的计算机仿真,研究了实际模型和估计模型之间的差异以及控制器的影响。然后针对不同的运行模式确定控制器参数。本方法允许控制器应用时变系统方程式所需的必要改变。

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