ARX, ARMAX, Box-Jenkins,输出误差,和Hammerstein模型建模智能气动执行器(IPA)系统

Mohamed Naji Muftah, Wong Liang Xuan, A. Faudzi
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引用次数: 4

摘要

气动执行机构具有高度非线性,难以实现精确的位置控制。为了实现精确控制,选择合适的模型结构是进行控制估计的前提。模型结构的选择是基于对物理系统的理解。本文选择黑盒模型作为系统辨识模型,对智能气动执行器(IPA)系统的位置控制及多种参数化模型结构进行建模。参数化模型结构,如ARX、ARMAX、Box-Jenkins、输出-误差结构、Hammerstein等可在黑盒模型中使用,以协助对IPA系统建模。结果表明,Hammerstein对IPA系统的位置控制建模效果最好,拟合最佳值为94.95。结果还表明,ARX、ARMAX、Box-Jenkins和output-error结构的拟合度最高可达90%以上。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ARX, ARMAX, Box-Jenkins, Output-Error, and Hammerstein Models for Modeling Intelligent Pneumatic Actuator (IPA) System
A pneumatic actuator is highly nonlinear, which makes the precise position control of this actuator difficult to achieve. In order to achieve precise control, selecting a suitable model structure is a prerequisite before control estimation. This selection of the model structure is based upon an understanding of the physical systems. In this paper, the black-box model is chosen as a system identification model for modeling position control of an Intelligent Pneumatic Actuator (IPA) system and a variety of parametric model structures. The parametric model structure, such as ARX, ARMAX, Box-Jenkins, output-error structures, and Hammerstein available in the black-box model, is used to assist in modeling the IPA system. The results indicate that Hammerstein had the best performance for modeling position control of the IPA system with the best fit 94.95. Also, the results show that ARX, ARMAX, Box-Jenkins, and output-error structures had best fit more than 90%.
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