No 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. And it is accepted that vortex-induced vibration (VIV) of 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.