Application of Finite-Frequency Model Reduction Method to Floating Wind Turbine

2021 ◽  
Vol 11 (11) ◽  
pp. 2742-2751
Author(s):  
海耀 马
2016 ◽  
Vol 203 ◽  
pp. 121-128 ◽  
Author(s):  
Da-Wei Ding ◽  
Xiangpeng Xie ◽  
Xin Du ◽  
Xiao-Jian Li

2016 ◽  
Vol 24 (6) ◽  
pp. 1464-1474 ◽  
Author(s):  
Da-Wei Ding ◽  
Xiao-Jian Li ◽  
Xin Du ◽  
Xiangpeng Xie

2021 ◽  
Vol 297 ◽  
pp. 01035
Author(s):  
Rachid Naoual ◽  
Abderrahim El-Amrani ◽  
Ismail Boumhidi

This paper deals with the problem of H∞ model reduction for two-dimensional (2D) discrete Takagi-Sugeno (T-S) fuzzy systems described by Fornasini-Marchesini local state-space (FM LSS) models, over finite frequency (FF) domain. New design conditions guaranteeing the FF H∞ model reduction are established in terms of Linear Matrix Inequalities (LMIs). To highlight the effectiveness of the proposed H∞ model reduction design, a numerical example is given.


2011 ◽  
Vol 219-220 ◽  
pp. 379-382
Author(s):  
Ling Fang Sun ◽  
Xiang Hua Meng ◽  
Fei Fei Zhang

A new kind of frequency model reduction method is proposed for unstable processes with time delay based on genetic algorithm. By adopting error between actual model and objective model, the model reduction process is transformed into minimal optimization process. To direct at time-delay problem, phase angle condition is introduced to increase degree of approximation between reduction model and actual model. Performance index is optimized with genetic algorithm to enlarge the applicability of traditional algorithm; the problem of model reduction is solved effectively with this method. Simulation results show that the reduced order model not only can approximate the original model but also can give good dynamic and static characteristics.


2021 ◽  
Vol 78 ◽  
pp. 102970
Author(s):  
B. Wiegard ◽  
M. König ◽  
J. Lund ◽  
L. Radtke ◽  
S. Netzband ◽  
...  

2021 ◽  
Vol 221 ◽  
pp. 108528
Author(s):  
Shengwen Xu ◽  
Motohiko Murai ◽  
Xuefeng Wang ◽  
Kensaku Takahashi

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