Robust identification approach for nonlinear state-space models

被引：10
|
作者：
Liu, Xin [1 ]
Yang, Xianqiang [1 ,2 ]
机构：
[1] Harbin Inst Technol, Sch Astronaut, Harbin 150080, Heilongjiang, Peoples R China
[2] Harbin Inst Technol, State Key Lab Robot & Syst, Harbin 150080, Heilongjiang, Peoples R China
来源：
NEUROCOMPUTING | 2019年 / 333卷
基金：
中国国家自然科学基金;
关键词：
Nonlinear system identification; Robustness; Student's t-distribution; Particle smoother; Expectation-maximization algorithm; SYSTEM-IDENTIFICATION; MULTIMODEL APPROACH; LPV APPROACH;
D O I：
10.1016/j.neucom.2018.12.017
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The identification of nonlinear state-space model (NSSM) with output observations corrupted by outliers is investigated in this paper. The outlier is commonly encountered in practical industrial processes which should not be ignored in nonlinear processes modeling. The statistical scheme based on the Student's t-distribution is applied to resist the outlier and the expectation-maximization (EM) algorithm is employed to simultaneously identify the undetermined model and noise parameters. A particle smoother is introduced and used to approximately calculate the desired Q-function. The usefulness of the proposed approach is demonstrated via the numerical and mechanical examples. (C) 2018 Elsevier B.V. All rights reserved.
引用
收藏
页码：329 / 338
页数：10
相关论文
共 50 条
  • [21] Robust identification of nonlinear time-delay system in state-space form
    Liu, Xin
    Yang, Xianqiang
    Zhu, Pengbo
    Xiong, Weili
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2019, 356 (16): : 9953 - 9971
  • [22] ROBUST STABILITY IN LINEAR STATE-SPACE MODELS
    JIANG, CL
    INTERNATIONAL JOURNAL OF CONTROL, 1988, 48 (02) : 813 - 816
  • [23] NONLINEAR-SYSTEM IDENTIFICATION USING NEURAL STATE-SPACE MODELS, APPLICABLE TO ROBUST-CONTROL DESIGN
    SUYKENS, JAK
    DEMOOR, BLR
    VANDEWALLE, J
    INTERNATIONAL JOURNAL OF CONTROL, 1995, 62 (01) : 129 - 152
  • [24] State-Space Models on the Stiefel Manifold with a New Approach to Nonlinear Filtering
    Yang, Yukai
    Bauwens, Luc
    ECONOMETRICS, 2018, 6 (04):
  • [25] A state-space approach to robust multiuser detection
    El-Keyi, Amr
    Kirubarajan, Thia
    Gershman, Alex B.
    IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2007, 6 (09) : 3333 - 3343
  • [26] State-space identification of nonlinear flight dynamics
    Lyshevski, SE
    PROCEEDINGS OF THE 1997 IEEE INTERNATIONAL CONFERENCE ON CONTROL APPLICATIONS, 1997, : 496 - 498
  • [27] A state-space approach to robust multiuser detection
    El-Keyi, A
    Kirubarajan, T
    Gershman, AB
    IEEE CAMSAP 2005: FIRST INTERNATIONAL WORKSHOP ON COMPUTATIONAL ADVANCES IN MULTI-SENSOR ADAPTIVE PROCESSING, 2005, : 145 - 148
  • [28] Learning nonlinear state-space models for control
    Raiko, T
    Tornio, M
    PROCEEDINGS OF THE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), VOLS 1-5, 2005, : 815 - 820
  • [29] Shooting methods for identification of nonlinear state-space grey-box models
    Retzler, Andras
    Swevers, Jan
    Gillis, Joris
    Kollar, Zsolt
    2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC), 2022, : 207 - 212
  • [30] CVA Identification of Nonlinear Systems with LPV State-Space Models of Affine Dependence
    Larimore, Wallace E.
    Cox, Pepijn B.
    Toth, Roland
    2015 AMERICAN CONTROL CONFERENCE (ACC), 2015, : 831 - 837
12345