Gaussian Process Regression for Nonlinear Time-Varying System Identification

被引：0
|
作者：
Bergmann, Daniel [1 ]
Buchholz, Michael [1 ]
Niemeyer, Jens [2 ]
Remele, Joerg [2 ]
Graichen, Knut [1 ]
机构：
[1] Ulm Univ, Inst Measurement Control & Microtechnol, Ulm, Germany
[2] MTU Friedrichshafen GmbH, Friedrichshafen, Germany
来源：
2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC) | 2018年
关键词：
D O I：
暂无
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 paper presents a method for nonlinear system identification with Gaussian process regression. The unsupervised method is able to generate an approximation of the system with correct extrapolation behaviour, that is refined with input/output-data in the typical working area and sampled online data. Therefore, an offline model is generated, which consists of a nominal model set up by the extrapolation behaviour and a detailed model for the refinement. The method is able to keep track of time-varying systems by using the confidence information to incorporate new measurements into the online model. The performance of the proposed method is tested on different numerical examples.
引用
收藏
页码：3025 / 3031
页数：7
相关论文
共 50 条
  • [21] How nonlinear system identification can benefit from recent time-varying tools: the time-varying best linear approximation
    Vanbeylen, Laurent
    Louarroudi, Ebrahim
    Pintelon, Rik
    2013 IEEE 52ND ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2013, : 4913 - 4918
  • [22] Online model regression for nonlinear time-varying manufacturing systems
    Hu, Jinwen
    Zhou, Min
    Li, Xiang
    Xu, Zhao
    AUTOMATICA, 2017, 78 : 163 - 173
  • [23] Incremental Gaussian Mixture Model for Time-varying Process Monitoring
    Dai, Qingyang
    Zhao, Chunhui
    PROCEEDINGS OF 2020 IEEE 9TH DATA DRIVEN CONTROL AND LEARNING SYSTEMS CONFERENCE (DDCLS'20), 2020, : 1305 - 1311
  • [24] Adaptive Control for Time-varying Nonlinear System
    Niu, Lin
    Chen, Bin
    Ye, Liaoyuan
    2009 INTERNATIONAL CONFERENCE ON COMPUTER AND AUTOMATION ENGINEERING, PROCEEDINGS, 2009, : 8 - +
  • [25] LYAPUNOV FUNCTION FOR A TIME-VARYING NONLINEAR SYSTEM
    MANDAL, AK
    IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 1972, AC17 (04) : 570 - &
  • [26] Parsimonious characterisation and identification of time-varying nonlinear systems
    Ralston, JC
    Zoubir, AM
    ISSPA 96 - FOURTH INTERNATIONAL SYMPOSIUM ON SIGNAL PROCESSING AND ITS APPLICATIONS, PROCEEDINGS, VOLS 1 AND 2, 1996, : 877 - 880
  • [27] IDENTIFICATION OF NONLINEAR CASCADE SYSTEMS WITH TIME-VARYING BACKLASH
    Voeroes, Jozef
    JOURNAL OF ELECTRICAL ENGINEERING-ELEKTROTECHNICKY CASOPIS, 2011, 62 (02): : 87 - 92
  • [28] Noise covariance identification for time-varying and nonlinear systems
    Ge, Ming
    Kerrigan, Eric C.
    INTERNATIONAL JOURNAL OF CONTROL, 2017, 90 (09) : 1903 - 1915
  • [29] Nonlinear time-varying model: Fuzzy parameter varying system
    Zhang H.-Y.
    Liang Y.
    Ban X.-J.
    Wu F.
    Ban, Xiao-Jun, 1600, Editorial Department of Electric Machines and Control (20): : 86 - 91
  • [30] IDENTIFICATION OF TIME-VARYING SYSTEM PARAMETERS.
    Brown III, James E.
    1972,
12345