Effective wind speed estimation: Comparison between Kalman Filter and Takagi-Sugeno observer techniques

被引:39
|
作者
Gauterin, Eckhard [1 ]
Kammerer, Philipp [1 ]
Kuehn, Martin [2 ]
Schulte, Horst [1 ]
机构
[1] HTW Univ Appl Sci Berlin, Dept Engn 1, Control Engn Grp, Wilhelminenhofstr 75a, D-12459 Berlin, Germany
[2] ForWind Univ Oldenburg, Inst Phys, Ammerlander Heerstr 136, D-26129 Oldenburg, Germany
关键词
Wind turbine control; Wind speed reconstruction; Takagi-Sugeno observer; Enhanced Kalman filter; Feedforward control; FUZZY REGULATORS;
D O I
10.1016/j.isatra.2015.11.016
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Advanced model-based control of wind turbines requires knowledge of the states and the wind speed. This paper benchmarks a nonlinear Takagi-Sugeno observer for wind speed estimation with enhanced Kalman Filter techniques: The performance and robustness towards model-structure uncertainties of the Takagi-Sugeno observer, a Linear, Extended and Unscented Kalman Filter are assessed. Hence the Takagi-Sugeno observer and enhanced Kalman Filter techniques are compared based on reduced-order models of a reference wind turbine with different modelling details. The objective is the systematic comparison with different design assumptions and requirements and the numerical evaluation of the reconstruction quality of the wind speed. Exemplified by a feedforward loop employing the reconstructed wind speed, the benefit of wind speed estimation within wind turbine control is illustrated. (C) 2015 ISA. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:60 / 72
页数:13
相关论文
共 50 条
  • [1] Takagi-Sugeno Fuzzy Observer and Extended-Kalman Filter for Adaptive Payload Estimation
    Beyhan, Selami
    Lendek, Zsofia
    Alci, Musa
    Babuska, Robert
    2013 9TH ASIAN CONTROL CONFERENCE (ASCC), 2013,
  • [2] Extended Kalman filter and Takagi-Sugeno fuzzy observer for a strip winding system
    Szedlak-Stinean, Alexandra-Iulia
    Precup, Radu-Emil
    Petriu, Emil M.
    Roman, Raul-Cristian
    Hedrea, Elena-Lorena
    Bojan-Dragos, Claudia-Adina
    EXPERT SYSTEMS WITH APPLICATIONS, 2022, 208
  • [3] Wind Turbine Model and Observer in Takagi-Sugeno Model Structure
    Georg, Soeren
    Mueller, Matthias
    Schulte, Horst
    SCIENCE OF MAKING TORQUE FROM WIND 2012, 2014, 555
  • [4] Takagi-Sugeno Fuzzy-based Kalman Filter Observer for Vehicle Side-slip Angle Estimation and Lateral Stability Control
    Zhang, Liqin
    Li, Boyuan
    Du, Haiping
    Zhang, Bangji
    2019 3RD INTERNATIONAL SYMPOSIUM ON AUTONOMOUS SYSTEMS (ISAS 2019), 2019, : 352 - 357
  • [5] Fault Estimation Based on Kalman Filtering for Takagi-Sugeno Fuzzy Systems
    Sun, Shaoxin
    Zhang, Huaguang
    Wang, Yingchun
    Han, Jian
    Wu, Jing
    2017 CHINESE AUTOMATION CONGRESS (CAC), 2017, : 1653 - 1658
  • [6] Takagi-Sugeno Sliding Mode Observer Design for Load Estimation and Sensor Fault Detection in Wind Turbines
    Schulte, Horst
    Zajac, Michal
    Georg, Soeren
    2012 IEEE INTERNATIONAL CONFERENCE ON FUZZY SYSTEMS (FUZZ-IEEE), 2012,
  • [7] Fuzzy Observer Design for State and Fault Estimation for Takagi-Sugeno Implicit Models
    Ouzaz, Manal
    El Assoudi, Abdellatif
    El Yaagoubi, El Hassane
    INTERNATIONAL JOURNAL OF FUZZY LOGIC AND INTELLIGENT SYSTEMS, 2023, 23 (01) : 1 - 10
  • [8] Observer Design for Motorcycle Lean and Steering Dynamics Estimation: a Takagi-Sugeno Approach
    Ichalal, Dalil
    Dabladji, Habib
    Arioui, Hichem
    Mammar, Said
    Nehaoua, Lamri
    2013 AMERICAN CONTROL CONFERENCE (ACC), 2013, : 5654 - 5659
  • [9] Disturbance Compensation by Wind Speed Reconstruction based on a Takagi-Sugeno Wind Turbine Model
    Gauterin, Eckhard
    Schulte, Horst
    Georg, Soeren
    SCIENCE OF MAKING TORQUE FROM WIND 2014 (TORQUE 2014), 2014, 524
  • [10] Zonotopic Kalman Observer-based Sensor Fault Estimation for Discrete-Time Takagi-Sugeno Fuzzy Systems
    Ren, Weijie
    Komada, Satoshi
    Yubai, Kazuhiro
    Yashiro, Daisuke
    2022 IEEE 17TH INTERNATIONAL CONFERENCE ON ADVANCED MOTION CONTROL (AMC), 2022, : 1 - 5