基于非线性反馈的 N$ 阶等效输入扰动复合方法

IF 5.2 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Xiang Yin;Jinhua She;Jingcheng Guo;Wei Guo;Gang Su
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引用次数: 0

摘要

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Composite Nonlinear Feedback-Based $N$-Order Equivalent-Input-Disturbance Approach
The equivalent-input-disturbance (EID) approach is effective to suppress the influences of disturbances. However, an EID-based control system suffers from severe fluctuations when an exogenous disturbance appears and disappears, which degrades the transient performance. This article uses the composite nonlinear feedback (CNF) to deal with such a problem and is the first time to do that. Moreover, an $n$-order low-pass filter is designed for the EID approach to improving the disturbance-rejection performance. Combining the $n$-order EID estimator with the CNF, a CNF-based $n$-order EID approach is presented, which not only improves the disturbance-rejection performance but also degrades the fluctuations of the system output when the disturbance appears and disappears. Analyzing the configuration of the $n$-order low-pass filter, this article finds and proves its general mathematical express using the mathematical induction method. Next, the stability analysis is broken into stability conditions of two subsystems. Then, the design of the $n$-order EID estimator is transformed into an optimization problem based on the stability conditions. Finally, the simulation results show the validity and superiority of the presented method.
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来源期刊
IEEE Open Journal of the Industrial Electronics Society
IEEE Open Journal of the Industrial Electronics Society ENGINEERING, ELECTRICAL & ELECTRONIC-
CiteScore
10.80
自引率
2.40%
发文量
33
审稿时长
12 weeks
期刊介绍: The IEEE Open Journal of the Industrial Electronics Society is dedicated to advancing information-intensive, knowledge-based automation, and digitalization, aiming to enhance various industrial and infrastructural ecosystems including energy, mobility, health, and home/building infrastructure. Encompassing a range of techniques leveraging data and information acquisition, analysis, manipulation, and distribution, the journal strives to achieve greater flexibility, efficiency, effectiveness, reliability, and security within digitalized and networked environments. Our scope provides a platform for discourse and dissemination of the latest developments in numerous research and innovation areas. These include electrical components and systems, smart grids, industrial cyber-physical systems, motion control, robotics and mechatronics, sensors and actuators, factory and building communication and automation, industrial digitalization, flexible and reconfigurable manufacturing, assistant systems, industrial applications of artificial intelligence and data science, as well as the implementation of machine learning, artificial neural networks, and fuzzy logic. Additionally, we explore human factors in digitalized and networked ecosystems. Join us in exploring and shaping the future of industrial electronics and digitalization.
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