Open AccessDesign of an individual pitch controller for offshore wind turbines based on neuro‐adaptive control
Author(s) -
Wang Lei,
Zhang Lei,
Ke Jianbo,
Fan Zeng,
Chen Jiawei,
Yang Wenxian
Publication year - 2020
Publication title -
iet renewable power generation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.005
H-Index - 76
eISSN - 1752-1424
pISSN - 1752-1416
DOI - 10.1049/iet-rpg.2020.0616
Subject(s) - control theory (sociology) , pitch control , turbine , pitch angle , controller (irrigation) , matlab , wind power , computer science , offshore wind power , wind speed , stability (learning theory) , tracking error , blade pitch , tracking (education) , control engineering , control (management) , engineering , mechanical engineering , agronomy , physics , electrical engineering , artificial intelligence , machine learning , geophysics , meteorology , biology , geology , operating system , psychology , pedagogy
For large offshore wind turbines, pitch control is usually used for regulating generated power to the rated value and for mitigating the dynamic loads that at the wind speeds above the rated speeds. However, tracking the pitch angle accurately and quickly can hardly be realised due to complex operating environments, uncertain system parameters, various disturbances, and coupled effects between wind, wave, and turbine structure. In this study, an individual pitch control system based on a neural adaptive strategy is proposed to address the problems related to uncertain system parameters and various disturbances. The proposed control method can achieve zero error tracking for the pitch angle in a predefined finite time. The design and stability analysis for the proposed method is elaborated. A simulation model is established in Matlab/Simulink, and by comparing it with the traditional proportional–integral–derivative control method, the merit of the proposed control scheme is verified.