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Adaptive fuzzy-neural-network control for induction spindle motor drive

机译:异步主轴电机驱动的自适应模糊神经网络控制

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摘要

An induction spindle motor drive using synchronous pulse-width modulation (PWM) and dead-time compensatory techniques with an adaptive fuzzy-neural-network controller (AFNNC) is proposed in this study for advanced spindle motor applications. First, the operating principles of a new synchronous PWM technique and the circuit of dead-time compensator are described in detail. Then, since the control characteristics and motor parameters for high-speed-operated induction spindle motor drive are time varying, an AFNNC is proposed to control the rotor speed of the induction spindle motor. In the proposed controller, the induction spindle motor-drive system is identified by a fuzzy-neural-network identifier (FNNI) to provide the sensitivity information of the drive system to an adaptive controller. The backpropagation algorithm is used to train the FNNI online. Moreover, the effectiveness of the proposed induction spindle motor-drive system is demonstrated using some simulated and experimental results.
机译:在这项研究中,提出了一种使用同步脉宽调制(PWM)和死区补偿技术以及自适应模糊神经网络控制器(AFNNC)的感应主轴电机驱动器,以用于高级主轴电机应用。首先,详细描述了一种新的同步PWM技术的工作原理以及死区时间补偿器的电路。然后,由于用于高速感应主轴电动机驱动的控制特性和电动机参数随时间变化,因此提出了一种AFNNC来控制感应主轴电动机的转子速度。在提出的控制器中,感应主轴电机驱动系统由模糊神经网络标识符(FNNI)标识,以将驱动系统的灵敏度信息提供给自适应控制器。反向传播算法用于在线训练FNNI。此外,通过一些模拟和实验结果证明了所提出的感应主轴电动系统的有效性。

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