Acceleration feedforward control in active magnetic bearing system subject to base motion by filtered-X LMS algorithm

被引:32
|
作者
Kang, MS [1 ]
Yoon, WH
机构
[1] Kyungwon Univ, Dept Mech Engn, Songnam 461701, Kyunggi Do, South Korea
[2] Kyungwon Univ, Grad Sch Ind & Environm, Songnam 461701, Kyunggi Do, South Korea
关键词
acceleration feedforward compensator; active magnetic bearing (AMB); adaptive estimation; base motion; disturbance; electromagnetic forces; feedforward compensation; filtered-x least mean square (FXLMS) algorithm; least mean square method;
D O I
10.1109/TCST.2005.847337
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This brief addresses the application of an active magnetic bearing (AMB) system to levitate the elevation axis of an electro-optical sight mounted on a moving vehicle. In this type of system, it is desirable to retain the elevation axis in an air-gap between magnetic bearing stators while the vehicle is moving. An optimal acceleration feedforward compensator design technique is proposed to attenuate disturbance responses in an AMB system that is subject to base motion. In consideration of the sensitivity of the disturbance compensation performance to the model accuracy, an experimental feedforward compensator is developed from an adaptive estimation by means of the filtered-x least mean square (FXLMS) algorithm. The compensation control is applied to a single degree of freddom (DOF) AMB system subject to base motion. The feasibility of the proposed technique is illustrated, and the results of an experimental demonstration are shown.
引用
收藏
页码:134 / 140
页数:7
相关论文
共 50 条
  • [1] A robust Filtered-x LMS algorithm for active vibration control
    Wang, Yong
    Fu, Zhihao
    Li, Xiaojian
    Pan, Jinwen
    Chen, Shaoqing
    2014 INTERNATIONAL CONFERENCE ON MECHATRONICS AND CONTROL (ICMC), 2014, : 279 - 283
  • [2] Optimal feedforward control of active magnetic bearing system subject-to base motion
    Kang, MS
    CCA 2003: PROCEEDINGS OF 2003 IEEE CONFERENCE ON CONTROL APPLICATIONS, VOLS 1 AND 2, 2003, : 748 - 753
  • [3] Stochastic Analysis of the Filtered-x LMS Algorithm for Active Noise Control
    Yang, Feiran
    Guo, Jianfeng
    Yang, Jun
    IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2020, 28 : 2252 - 2266
  • [4] Active vibration control of a structure by implementing filtered-X LMS algorithm
    Gupta, A.
    Yandamuri, S.
    Kuo, S. M.
    NOISE CONTROL ENGINEERING JOURNAL, 2006, 54 (06) : 396 - 405
  • [5] A TWIN-REFERENCE COMPLEX FILTERED-X LMS ALGORITHM FOR FEEDFORWARD ACTIVE NOISE CONTROL AND ITS CONVERGENCE
    Hinamoto, Yoichi
    Doi, Akimitsu
    2011 IEEE 54TH INTERNATIONAL MIDWEST SYMPOSIUM ON CIRCUITS AND SYSTEMS (MWSCAS), 2011,
  • [6] Kernel Filtered-x LMS Algorithm for Active Noise Control System with Nonlinear Primary Path
    Liu, Yuqi
    Sun, Chao
    Jiang, Shouda
    CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2018, 37 (12) : 5576 - 5594
  • [7] Kernel Filtered-x LMS Algorithm for Active Noise Control System with Nonlinear Primary Path
    Yuqi Liu
    Chao Sun
    Shouda Jiang
    Circuits, Systems, and Signal Processing, 2018, 37 : 5576 - 5594
  • [8] Adaptive Filtered-X LMS Algorithm for Active Vibration Control on Micron Positioning Stage
    Liu, Yun-Hui
    Lee, Hong-Jen
    2012 INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND INFORMATION SCIENCES (ICCAIS), 2012, : 370 - 374
  • [9] Time-frequency-domain filtered-x LMS algorithm for active noise control
    Tang, X. L.
    Lee, C. -M.
    JOURNAL OF SOUND AND VIBRATION, 2012, 331 (23) : 5002 - 5011
  • [10] Analysis of the filtered-X LMS algorithm and a related new algorithm for active control of multitonal noise
    Hinamoto, Y
    Sakai, H
    IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2006, 14 (01): : 123 - 130