Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/88961
Title: A simple discrete-time tracking differentiator and its application to speed and position detection system for a maglev train
Authors: Zhang, Hehong
Xie, Yunde
Xiao, Gaoxi
Zhai, Chao
Long, Zhiqiang
Keywords: DRNTU::Engineering::Electrical and electronic engineering
Filter
Discrete Time
Issue Date: 2018
Source: Zhang, H., Xie, Y., Xiao, G., Zhai, C., & Long, Z. (2019). A simple discrete-time tracking differentiator and its application to speed and position detection system for a maglev train. IEEE Transactions on Control Systems Technology, 27(4), 1728-1734. doi:10.1109/TCST.2018.2832139
Series/Report no.: IEEE Transactions on Control Systems Technology
Abstract: In this brief, a novel tracking differentiator (TD) based on discrete time optimal control (DTOC) is presented. In particular, using the state back-stepping method, a DTOC law for a discrete-time, double-integral system is determined by linearized criterion, which equips the TD with a simple structure. The analysis of the proposed TD reveals its filtering mechanism. Simulation results show that it performs well in signal tracking and differentiation acquisition, and reduces the computational resources needed. Experiments conducted on the speed and position detection system for a maglev train demonstrate that the proposed TD group, with moving average algorithm, can filter noises, amend distortion signals effectively, and compensate for phase delays when the train is passing over track joints.
URI: https://hdl.handle.net/10356/88961
http://hdl.handle.net/10220/48905
ISSN: 1063-6536
DOI: http://dx.doi.org/10.1109/TCST.2018.2832139
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TCST.2018.2832139
Fulltext Permission: open
Fulltext Availability: With Fulltext
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