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Contouring accuracy improvement of a piezo-actuated micro motion stage based on fuzzy cerebellar model articulation controller

机译:基于模糊小脑模型关节控制器的压电微动平台轮廓精度的提高

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摘要

The motion accuracy and performance of piezoelectric actuators (PEA) are hampered by their inherent hysteresis nonlinearity and time-varying parameters. In order to overcome these drawbacks, an integrated motion control scheme is developed in this paper. In the proposed controller scheme, for each axis of the micro motion stage, a fuzzy CMAC feedforward controller combined with a conventional proportional-integral (PI) feedback controller and a critic-based learning mechanism (FCMAC-CLM) is used to improve the tracking performance and deal with the adverse effects due to hysteresis nonlinearity and external disturbance. In addition, one of the most important issues in the contour following tasks performed by a dual-axis micro motion stage is the contour error reduction. In order to improve the contouring accuracy, a fuzzy CMAC that is capable of real-time learning and self-adjusting is exploited to develop a fuzzy CMAC cross-coupled controller (FCMAC-CCC). Several experiments have been conducted to evaluate the tracking performance and contour accuracy of the proposed approach.
机译:压电致动器(PEA)的运动精度和性能受到其固有的磁滞非线性和时变参数的影响。为了克服这些缺点,本文开发了一种集成运动控制方案。在提出的控制器方案中,对于微运动级的每个轴,模糊CMAC前馈控制器与常规比例积分(PI)反馈控制器和基于批评者的学习机制(FCMAC-CLM)结合在一起用于改善跟踪性能并处理由于磁滞非线性和外部干扰引起的不利影响。此外,双轴微动位移台执行的轮廓跟随任务中最重要的问题之一就是轮廓误差的减小。为了提高轮廓精度,利用具有实时学习和自我调节能力的模糊CMAC来开发模糊CMAC交叉耦合控制器(FCMAC-CCC)。已经进行了一些实验来评估所提出方法的跟踪性能和轮廓精度。

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