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A Speed Control System of Permanent Magnet Linear Synchronous Motor Using Neuron Adaptive Controller

机译:基于神经元自适应控制器的永磁直线同步电动机速度控制系统。

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The neuron net has ability to self-learning and adaptation,so its appfication into control does not depends on mathematic model of control object, and the neuron net controller can overcome the defect of less robustness of the conventional PI controller while changing of motor parameters.It is proposed to apply the neuron net control method into control system of the permanent magnet linear synchronous motor (PMLSM). In this thesis,a neuron adaptive controller is designed according to nonlinear and uncertainty of the PMLSM as speed controller.The dynamic equation of the PMLSM feeding system is obtained by analyzing PMLSM d-q modeL The simulation experiment has been made under the condition of starting and loading of motor.The results has shown that PMLSM Control System Based on Neuron adaptive Controller has not only good dynamic and stable performance, but also better robustness than PI control system.
机译:神经网络具有自学习和自适应的能力,因此其在控制中的应用不依赖于控制对象的数学模型,神经网络控制器可以克服传统PI控制器在改变电机参数时鲁棒性较弱的缺点。提出将神经元网络控制方法应用于永磁直线同步电动机(PMLSM)的控制系统。本文根据PMLSM的非线性和不确定性,设计了一种神经元自适应控制器作为速度控制器。通过分析PMLSM dq modeL得到了PMLSM进给系统的动力学方程。结果表明,基于神经元自适应控制器的PMLSM控制系统不仅具有良好的动态和稳定性能,而且比PI控制系统具有更好的鲁棒性。

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