Open AccessApplication of Improved Particle Swarm Optimization Algorithm in Parameter Identification of Pitch Wind Turbine System
Author(s) -
Huanhui Zhou,
Hao Zhang
Publication year - 2019
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.179
H-Index - 26
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/295/4/042129
Subject(s) - particle swarm optimization , convergence (economics) , identification (biology) , adaptability , multi swarm optimization , algorithm , turbine , system identification , control theory (sociology) , computer science , mathematical optimization , mathematics , engineering , artificial intelligence , data modeling , aerospace engineering , ecology , botany , control (management) , database , economics , biology , economic growth
The application of particle swarm optimization algorithm in parameter identification has a good performance, but there are still some problems such as partial localization and slow convergence. In this paper, the complex multi-parameter problem of the pitch wind turbine system is presented. The improved particle swarm optimization algorithm is used to identify the parameters and reconstruct the model. In the parameter identification, the parameter identification strategy of the descending dimension and the contraction boundary is proposed, and the accurate identification effect is obtained. In model reconstruction, adaptability is verified.