基于新型跟踪微分器的磁悬浮系统控制。

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2024-08-01 DOI:10.1016/j.isatra.2024.05.037
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引用次数: 0

摘要

本研究提出了一种新型跟踪微分器,并将其应用于滑模控制(SMC)算法,以解决磁悬浮系统干扰抑制效果不理想和跟踪精度低的问题。首先,为了评估滤波、跟踪和微分方面的性能,引入了反双曲正弦函数和两相功率函数来改进跟踪微分器。这可以加快全局收敛速度,确保在平衡点平稳收敛,减少系统抖动,并增强系统的噪声抑制能力。微分器参数调整规则来自系统扫描。仿真结果比较表明,所提出的微分器能有效抑制噪声,并能进行信号跟踪和微分。最后,新微分器被应用于磁悬浮系统的 SMC。仿真和实验结果表明,在基于新跟踪微分器的 SMC 下,磁悬浮系统的响应速度高,抖动有效降低,噪声抑制能力提高。
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Magnetic levitation system control based on a novel tracking differentiator

This study proposes a novel tracking differentiator and applies it to the sliding-mode control (SMC) algorithm to address the unsatisfactory disturbance suppression and low tracking accuracy of magnetic levitation (maglev) systems. First, to assess performance in terms of filtering, tracking, and differentiation, an inverse hyperbolic sine function and a two-phase power function are introduced to improve the tracking differentiator. This can accelerate the global convergence speed, ensure smooth convergence at the equilibrium point, reduce system jitter, and enhance the noise-suppression ability of the system. The differentiator parameter-adjustment rules are derived from a system sweep. A comparison of the simulation results show that the proposed differentiator effectively suppresses noise and performs signal tracking and differentiation. Finally, the new differentiator is applied to the SMC of a maglev system. Simulation and experimental results show that the response speed of the maglev system under the SMC based on the new tracking differentiator is high, the jitter is effectively reduced, and the noise-suppression ability is improved.

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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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