Open AccessAdaptive fault‐tolerant control of variable pitch system of wind power generator based on clustering‐type fuzzy neural network
Author(s) -
Wang Hongwei,
Zhang Qian
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.2020.0177
Subject(s) - control theory (sociology) , fault (geology) , wind power , computer science , electric power system , artificial neural network , pitch control , cluster analysis , induction generator , control engineering , fuzzy control system , fuzzy logic , engineering , power (physics) , control (management) , artificial intelligence , physics , quantum mechanics , seismology , electrical engineering , geology
In view of the faults of the doubly‐fed wind power generator system, the health situations of the system are described by the health factor functions. On this basis, the model reference adaptive fault‐tolerant control method based on clustering‐type fuzzy neural network is proposed. The proposed method can solve the adaptive control issues of wind power generator system with actuator faults, external interference and model uncertainties. The stability and the tracking performance of the system are guaranteed by using Lyapunov stability theorem. Finally, the effectiveness of the proposed method is proved by the fault‐tolerant control of the pitch system of the doubly‐fed wind power generator.