On Multi-Input Multi-Output Repetitive Control Design Methods

被引:0
|
作者
Longman, Richard W. [2 ]
Juang, Jer-Nan [1 ,4 ]
Phan, Minh Q. [3 ]
Xu, Kevin [5 ]
机构
[1] Natl Cheng Kung Univ, Dept Engn Sci, Tainan 70101, Taiwan
[2] Columbia Univ, Dept Mech Engn, New York, NY 10027 USA
[3] Dartmouth Coll, Thayer Sch Engn, Hanover, NH 03755 USA
[4] Texas A&M Univ, Aerosp Dept, College Stn, TX 77843 USA
[5] Columbia Univ, Dept Elect Engn, New York, NY 10027 USA
关键词
repetitive learning control; FIR compensator; frequency response based design; SYSTEMS; CONVERGENCE;
D O I
暂无
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
Repetitive control (RC) can address the common spacecraft jitter problem for fine pointing equipment resulting from small imbalance in reaction wheels or control momentum gyros (CMG). This problem requires multi-input, multi-output (MIMO) RC design methods. Previous papers by the authors developed a rather comprehensive stability theory for MIMO repetitive control, and suggest design methods whose performance is studied here. One approach stays on the MIMO level and minimizes a Frobenius norm summed over frequencies from zero to Nyquist. And it produces a matrix compensator composed of finite impose response (FIR) filters. The second approach reduces the problem to a set of SISO design problems, one for each input-output pair. The latter approach allows one to make use of experience gained in SISO designs. Both approaches are seen here to be able to create RC designs with fast monotonic decay of the tracking error. Choice of the FIR filter order and the choice of the number of non-causal gains, although critical in some SISO low order designs, does not appear to be an important issue in MIMO designs using reasonably large order.
引用
收藏
页码:477 / 492
页数:16
相关论文
共 50 条
  • [21] A multi-input multi-output control strategy for intelligent nonholonomic robots
    Li, Xiaolong
    Xian, Xiaodong
    Yuan, Yupeng
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 4698 - 4703
  • [22] Modelling and control of a twin rotor multi-input multi-output system
    Ahmad, SM
    Chipperfield, AJ
    Tokhi, MO
    PROCEEDINGS OF THE 2000 AMERICAN CONTROL CONFERENCE, VOLS 1-6, 2000, : 1720 - 1724
  • [23] Multi-input multi-output aeroelastic control using the receptance method
    Mokrani, B.
    Palazzo, F.
    Fichera, S.
    Adamson, L.
    Mottershead, J. E.
    PROCEEDINGS OF INTERNATIONAL CONFERENCE ON NOISE AND VIBRATION ENGINEERING (ISMA2018) / INTERNATIONAL CONFERENCE ON UNCERTAINTY IN STRUCTURAL DYNAMICS (USD2018), 2018, : 153 - 163
  • [24] Limit strategy for multi-input multi-output random vibration control
    Zheng, Ronghui
    Xie, Wenwei
    Wei, Xiaohui
    Chen, Huaihai
    MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2023, 195
  • [25] Observer design for a class of multi-input multi-output nonlinear systems
    Dong, Yali
    Yang, Yingjuan
    INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE, 2011, 42 (04) : 695 - 703
  • [26] Model design and data analysis for multi-input multi-output systems
    Nakazawa, D
    Trunov, A
    INTERNATIONAL CONFERENCE ON INTEGRATION OF KNOWLEDGE INTENSIVE MULTI-AGENT SYSTEMS: KIMAS'03: MODELING, EXPLORATION, AND ENGINEERING, 2003, : 368 - 374
  • [27] Stable multi-input multi-output adaptive fuzzy neural control
    Ordóñez, R
    Passino, KM
    IEEE TRANSACTIONS ON FUZZY SYSTEMS, 1999, 7 (03) : 345 - 353
  • [28] Investigating the multi-input multi-output air conditioning control techniques
    Pasha M.M.K.
    El-Fawal M.M.
    Journal Europeen des Systemes Automatises, 2020, 53 (03): : 345 - 355
  • [29] Time Decision for Multi-Input and Multi-Output Networked Control Systems
    Wang, Cailu
    Tao, Yuegang
    Shi, Ling
    IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS, 2020, 7 (02): : 558 - 567
  • [30] Multi-input Multi-Output Identification for Control of Adaptive Optics Systems
    Muradore, Riccardo
    Kolb, Johann
    Pettazzi, Lorenzo
    Marchetti, Enrico
    ADAPTIVE OPTICS SYSTEMS IV, 2014, 9148