基于干扰的等效输入控制:分析、开发和应用》。

IF 9.4 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Xiang Yin;Yuntao Shi;Jinhua She;Hanping Wang
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引用次数: 0

摘要

本文回顾了等效输入干扰(EID)方法的概念、分析、发展和应用。首先,给出了 EID 的定义和存在,并提供了 EID 估计器的配置。接着,解释了传统 EID 方法中的估计误差,并展示了误差抑制方法,这些方法提高了干扰抑制性能。然后,本文介绍了如何应用 EID 方法,以及在处理非线性、时间延迟和不确定性时遇到的相关挑战。此外,本文还回顾了一些无法归入上述类别的其他有意义的研究。最后,本文给出了一些结论和未来发展方向。EID 方法已成功用于抑制许多控制系统中的外生干扰、非线性、时间延迟和不确定性的影响,从而提高控制性能和鲁棒性。未来的研究可以进一步丰富 EID 方法的理论,如设计评价指标、提高干扰抑制性能、开发新的应用以及与其他控制理论相结合。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Equivalent Input Disturbance-Based Control: Analysis, Development, and Applications
This article reviews the concept, analysis, development, and applications of the equivalent-input-disturbance (EID) approach. First, the definition and existence of the EID are given, and the configuration of the EID estimator is provided. Next, estimation errors in the conventional EID approach are explained, and error-suppression methods are exhibited, which improve the disturbance-rejection performance. Then, this article describes how to apply the EID approach and associate challenges in dealing with nonlinearities, time delays, and uncertainties. Moreover, this article reviews some additional meaningful studies that cannot be categorized into the above-mentioned classes. Finally, some conclusions and future directions are given. The EID approach has been successfully used to suppress the influences of exogenous disturbances, nonlinearities, time delays, and uncertainties in many control systems to improve control performance and robustness. Studies can further rich the theory of the EID approach in the future, such as designing evaluation index, improving disturbance-rejection performance, developing new applications, and combining with other control theory.
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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