Affiliation:
1. School of Mechanical and Precision Instrument Engineering, Xi'an University of Technology, Xi'an 710048, China
2. School of Mechanical and Electrical Engineering, Guilin University of Electronic Technology, Guilin 5411004, China
Abstract
Given the great potential of the offshore wind power generation in renewable energy sources, it will bring unprecedented significant development opportunities. Meanwhile, the installed capacity of floating wind turbines (FWTs) is huge. However, as one of the important parts of that, FWTs are always subjected to complex environmental loads during operation, which will critically affect the stability of wind power generation. Hence, it is urgent to analyze and control its stability for the safe operation of wind turbines. It is accepted that vortex-induced vibration (VIV) of a bluff body structure is the leading cause of structural damage to FWTs. For this reason, a radial basis function neural network sliding mode control (RBFNNSMC) is proposed to improve the modeling accuracy of bluff body VIV control. Then, the joint numerical analysis system was designed to achieve the completely coupled fluid structure vibration control of bluff body. The numerical results indicate that RBFNNSMC can better control the forward/cross-flow vibration of bluff body. In addition, the controller is not responsive to changes in system parameters and has strong robustness.
Funder
National Natural Science Foundation of China
Ph.D Innovation found projects of Xi'an University of Technology
Subject
Condensed Matter Physics,Fluid Flow and Transfer Processes,Mechanics of Materials,Computational Mechanics,Mechanical Engineering
Cited by
6 articles.
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