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模拟复合正交神经网络在轴向磁轴承中的控制研究

Control study of analog compound orthogonal neural network in axial magnetic bearing
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摘要 由于磁轴承的动态性能主要取决于所采用的控制规律,控制器是磁轴承系统的关键。在数字复合正交神经网络(NN)的基础上,提出了一种模拟复合正交神经网络,并用于轴向磁轴承的控制中。控制器采用模拟复合正交神经网络与PID的并行控制方法,对带有负载干扰的轴向磁轴承控制系统作了PID控制与NN+PID控制的仿真实验。仿真结果表明,相对于常规PID控制器,该并行控制法具有较高的抗干扰与自适应能力,控制效果理想。 The dynamic properties are mostly decided by the controller, so the control method is key of active magnetic bearing. An analog compound orthogonal neural network (NN) was presented on the basis of the digital compound orthogonal neural network and was applied in the control of the axial magnetic bearing. The controller was a parallel control method with an analog compound orthogonal neural network and PID. Simulation experiments were given for control system of the axial magnetic bearing with load disturbance by using PID controller and NN + PID controller. The simulation results prove that the parallel control method has excellent anti-disturbance and speed response ability by comparison with PID controller, and obtains satisfactory control effect.
出处 《机电工程》 CAS 2007年第8期73-75,共3页 Journal of Mechanical & Electrical Engineering
关键词 轴向磁轴承 模拟复合正交神经网络 连续学习算法 并行控制 axial magnetic bearing analog compound orthogonal neural network continuously learning algorithm parallel control
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