田口调谐径向基函数在高精度运动控制中的应用

K.K. Tan, K.Z. Tang
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引用次数: 4

摘要

本文提出了一种新的应用Taguchi方法对径向基函数(RBF)网络的权值进行系统整定的方法。径向基函数(RBF)网络广泛用于模糊但光滑的非线性函数建模。该方法的主要优点是统计设计过程定义明确,系统,便于实际实施。为了说明田口调优RBF的有效性,需要一个测试平台。该方法应用于高精度运动控制平台。将该方法应用于高精度运动环境下的基于rbf自适应控制的复合运动控制器的整定。仿真和实验结果表明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Taguchi-tuned radial basis function with application to high precision motion control

This paper presents a novel application of Taguchi method to systematically tune the weights of a radial basis function (RBF) network, which is widely used for modelling vaguely defined but smooth nonlinear functions. The main strength of this method is the well-defined and systematic statistical design procedure, which is amenable to practical implementation. To illustrate the effectiveness of the Taguchi-tuned RBF, a test platform is required. This approach is applied to a platform involving high precision motion control. The developed method then is used to tune a composite motion controller incorporating RBF-based adaptive control in a high precision motion environment. Simulation and experimental results reveal the effectiveness of a Taguchi-tuned RBF.

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