机电系统鲁棒估计的变结构和滑模滤波器研究

S. Andrew Gadsden, M. Al-Shabi
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引用次数: 24

摘要

本文对基于变结构和滑模理论的估计策略进行了研究。平滑变结构滤波器(SVSF)和新型滑动创新滤波器(SIF)基于相似的滑模概念,但有一些显著的区别。对相关文献和背景进行了研究,并介绍了svm和SIF估计算法。为了比较,本文将这两种估计策略应用于一个机电系统。结果表明,尽管SVSF和SIF都提供了对故障的鲁棒估计,但SIF公式在保持鲁棒性的同时提供了更准确的估计,并且计算复杂度更低。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Study of Variable Structure and Sliding Mode Filters for Robust Estimation of Mechatronic Systems
In this paper, a study of estimation strategies based on variable structure and sliding mode theory is performed. The smooth variable structure filter (SVSF) and the new sliding innovation filter (SIF) are based on similar sliding mode concepts but with some notable differences. The relevant literature and background are explored and the SVSF and SIF estimation algorithms are presented. For comparison purposes, the two estimation strategies are applied on a mechatronic system. The results indicate that although both the SVSF and SIF provide robust estimates to faults, the SIF formulation provides slightly more accurate estimates while maintaining robustness, and is less computationally complex.
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