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Control of Magnetic Suspended Flywheel using adaptive linear neuron

机译:自适应线性神经元控制磁悬浮飞轮

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Focused on robustness, low power consumption and unbalance compensation demands from Magnetic Suspended Flywheel (MSF), a network controller is presented using on adaptive linear neuron, and characteristic equation is derived and discussed form the point of stability, then, a method to ensure close loop stability is established by checking the update of neural network weight. Simulations are performed based on MSF nonlinear model, the results indicate that rapid response, low power consumption and robustness is achieved by the adaptive linear neuron control, unbalance vibration is eliminated under the constraints of power consumption, besides, the stability of close loop system is guaranteed by the weight update checking method.
机译:针对磁悬浮飞轮(MSF)的鲁棒性,低功耗和不平衡补偿需求,提出了一种基于自适应线性神经元的网络控制器,并从稳定性的角度推导并讨论了特征方程,然后提出了一种确保闭合的方法通过检查神经网络权重的更新来建立回路稳定性。基于MSF非线性模型进行仿真,结果表明,自适应线性神经元控制可实现快速响应,低功耗和鲁棒性,在功耗约束下消除了不平衡振动,并且闭环系统具有稳定性。权重更新检查方法保证。

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