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Design of a hybrid controller for voice coil motors with simple self-learning fuzzy control

机译:具有简单自学模糊控制的音箱电机混合控制器的设计

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The voice coil motor (VCM) has many excellent features such as high-starting thrust force, silence, low-cost and so on. In this paper, the dynamics of a VCM with the introduction of a lumped uncertainty is studied. It shows that the dynamic characteristics and motor parameters of the VCM are non-linear and time-varying. To resolve this problem, this paper proposes a hybrid control system, which comprised of a PD controller and simple self-learning fuzzy controller (SSFC), for the position tracking control of a VCM. The SSFC contains two sets of fuzzy inference system. One is the fuzzy controller and the other is the rule modifier. The modification value of each fuzzy rule is based on the fuzzy firing weight of each fuzzy rule to achieve satisfactory learning performance, thus it is suitable for on-line VCM control. Finally, the proposed hybrid control system is implemented on a 32-bit microcontroller for possible low-cost and high-performance industrial applications. The experimental results show that the proposed hybrid control system can achieve favorable tracking performance and is robust against payload variations of a VCM.
机译:音圈电机(VCM)具有许多优异的功能,如高启动推力,沉默,低成本等。本文研究了与引入集体不确定性的VCM动态。它表明,VCM的动态特性和电动机参数是非线性的和时变的。为了解决这个问题,本文提出了一种混合控制系统,其包括PD控制器和简单的自学习模糊控制器(SSFC),用于VCM的位置跟踪控制。 SSFC包含两组模糊推理系统。一个是模糊控制器,另一个是规则修饰符。每个模糊规则的修改值是基于每个模糊规则的模糊射击权重,以实现令人满意的学习性能,因此它适用于在线VCM控制。最后,提出的混合控制系统在32位微控制器上实现,以实现低成本和高性能的工业应用。实验结果表明,所提出的混合控制系统可以实现有利的跟踪性能,并且对VCM的有效载荷变化具有稳健性。

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