SYSDYNET - A MATLAB App and Toolbox for Dynamic Network Identification

被引:0
|
作者
Van den Hof, Paul M. J. [1 ]
Shi, Shengling [1 ]
Weerts, Harm H. M. [1 ]
Cheng, Xiaodong [1 ]
Ramaswamy, Karthik R. [1 ]
Dankers, Arne G. [1 ]
Dreef, H. J. [1 ]
Fonken, Stefanie J. M. [1 ]
Steentjes, Tom R. V. [1 ]
Meijer, Job B. T. [1 ]
机构
[1] Eindhoven Univ Technol, Dept Elect Engn, Control Syst Grp, Eindhoven, Netherlands
来源
IFAC PAPERSONLINE | 2024年 / 58卷 / 15期
关键词
System identification; identifiability; dynamic networks; interconnected systems; COMPLEX NETWORKS; IDENTIFIABILITY; MODULE; MODELS;
D O I
10.1016/j.ifacol.2024.08.591
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Identification in interconnected systems requires the handling of phenomena that go beyond the classical open-loop and closed-loop type of identification problems. Over the last decade a comprehensive theory has been developed for addressing identification problems in linear dynamic networks, formulated in a module framework, where the network structure is characterized by a directed graph in which nodes are signals and links are transfer functions. The resulting methods and approaches have been collected in a MATLAB App and Toolbox, supported by an attractive graphical user interface that provides an interactive workflow for manipulating the structural properties of dynamic networks, applying basic network operations like immersion and module invariance testing, and for investigating network/module generic identifiability and selecting appropriate predictor model inputs and outputs. The workflow supports the allocation of external excitation signals (actuation) and measured node signals (sensing) so as to achieve generic identifiability and provide consistent estimation of target modules. The Toolbox includes algorithms for actual network simulation and identification. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licneses/by-nc-nd/4.0/)
引用
收藏
页码:574 / 579
页数:6
相关论文
共 50 条
  • [21] Introduction of the MATLAB toolbox
    Yang, J.-Q.
    Luo, X.-X.
    Shuikexue Jinzhan/Advances in Water Science, 2001, 12 (02): : 237 - 242
  • [22] Matlab Laser Toolbox
    Romer, G. R. B. E.
    in 't Veld, A. J. Huis
    LASER ASSISTED NET SHAPE ENGINEERING 6, PROCEEDINGS OF THE LANE 2010, PART 2, 2010, 5 : 413 - 419
  • [23] A robotics toolbox for MATLAB
    Corke, PI
    IEEE ROBOTICS & AUTOMATION MAGAZINE, 1996, 3 (01) : 24 - 32
  • [24] MIMO Toolbox for Matlab
    Vivero, Oskar
    Liceaga-Castro, Jesus
    2008 ANNUAL IEEE STUDENT PAPER CONFERENCE, 2008, : 130 - +
  • [25] The Biodata toolbox for MATLAB
    De Gussem, K.
    De Gelder, J.
    Vandenabeele, P.
    Moens, L.
    CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS, 2009, 95 (01) : 49 - 52
  • [26] The CRONE toolbox for Matlab
    Oustaloup, A
    Melchior, P
    Lanusse, P
    Cois, O
    Dancla, F
    PROCEEDINGS OF THE 2000 IEEE INTERNATIONAL SYMPOSIUM ON COMPUTER-AIDED CONTROL SYSTEM DESIGN, 2000, : 190 - 195
  • [27] The GMT/MATLAB Toolbox
    Wessel, Paul
    Luis, Joaquim F.
    GEOCHEMISTRY GEOPHYSICS GEOSYSTEMS, 2017, 18 (02): : 811 - 823
  • [28] Frequency Domain System Identification toolbox for Matlab:: Improvements and new possibilities
    Kollár, I
    Pintelon, R
    Schoukens, J
    (SYSID'97): SYSTEM IDENTIFICATION, VOLS 1-3, 1998, : 943 - 946
  • [29] Dynamic Optimization of Guided Missile Trajectory by Use of Matlab and Dynopt Toolbox
    Ozana, Stepan
    Pies, Martin
    Wagner, Petr
    2012 12TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS), 2012, : 908 - 912
  • [30] Red mud thickener statistical model in MATLAB system identification toolbox
    Fedorova, E. R.
    Trifonova, M. E.
    Mansurova, O. K.
    INTERNATIONAL CONFERENCE: INFORMATION TECHNOLOGIES IN BUSINESS AND INDUSTRY, 2019, 1333