Recursive Subspace identification for time-varying continuous-time stochastic systems via distribution theory

被引：0
作者：
Yu, Miao [1 ]
Liu, Jianchang [2 ,3 ]
Wang, Honghai [2 ,3 ]
机构：
[1] Northeastern Univ Qinhuangdao, Sch Control Engn, Qinhuangdao 066004, Hebei, Peoples R China
[2] Northeastern Univ, Coll Informat Sci & Engn, Shenyang 110819, Peoples R China
[3] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang 110819, Peoples R China
来源：
2019 IEEE SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE (IEEE SSCI 2019) | 2019年
基金：
中国国家自然科学基金;
关键词：
Distribution theory; Recursive subspace identification; Time-varying system; Stochastic system; MODEL IDENTIFICATION; PREDICTION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes a recursive subspace identification method for time-varying continuous-time stochastic systems based on distribution theory. By using the random distribution theory, the time-derivative of stochastic processes is described and the input-output matrix equation is obtained. Moreover, we reduce the storage cost and computation burden by keeping the size of input-output data to be constant. Further, the system model is obtained. The simulation results show the validity and accuracy of the proposed method.
引用
收藏
页码：1310 / 1313
页数：4
相关论文
共 18 条
  • [1] Identification of step response estimates utilizing continuous time subspace approach
    Aziz, Muhammad Hilmi R. A.
    Mohd-Mokhtar, Rosmiwati
    Wang, Liuping
    [J]. JOURNAL OF PROCESS CONTROL, 2013, 23 (03) : 254 - 270
  • [2] A PMF-based subspace method for continuous-time model identification. Application to a multivariable winding process
    Bastogne, T
    Garnier, H
    Sibille, P
    [J]. INTERNATIONAL JOURNAL OF CONTROL, 2001, 74 (02) : 118 - 132
  • [3] Tensor network subspace identification of polynomial state space models
    Batselier, Kim
    Ko, Ching-Yun
    Wong, Ngai
    [J]. AUTOMATICA, 2018, 95 : 187 - 196
  • [4] Continuous-time predictor-based subspace identification using Laguerre filters
    Bergamasco, M.
    Lovera, M.
    [J]. IET CONTROL THEORY AND APPLICATIONS, 2011, 5 (07) : 856 - 867
  • [5] Recursive subspace system identification for parametric fault detection in nonlinear systems
    Gil, P.
    Santos, F.
    Palma, L.
    Cardoso, A.
    [J]. APPLIED SOFT COMPUTING, 2015, 37 : 444 - 455
  • [6] Predictor-Based Tensor Regression (PBTR) for LPV subspace identification
    Gunes, Bilal
    van Wingerden, Jan-Willem
    Verhaegen, Michel
    [J]. AUTOMATICA, 2017, 79 : 235 - 243
  • [7] Recursive subspace identification subject to relatively slow time-varying load disturbance
    Hou, Jie
    Liu, Tao
    Wang, Qing-Guo
    [J]. INTERNATIONAL JOURNAL OF CONTROL, 2018, 91 (03) : 622 - 638
  • [8] Recursive Predictor-Based Subspace Identification With Application to the Real-Time Closed-Loop Tracking of Flutter
    Houtzager, Ivo
    van Wingerden, Jan-Willem
    Verhaegen, Michel
    [J]. IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2012, 20 (04) : 934 - 949
  • [9] Subspace identification with moment matching
    Inoue, Masaki
    [J]. AUTOMATICA, 2019, 99 : 22 - 32
  • [10] Subspace-based prediction of linear time-varying stochastic systems
    Kameyama, Kentaro
    Ohsumi, Akira
    [J]. AUTOMATICA, 2007, 43 (12) : 2009 - 2021
12