Bifurcation Analysis of a Wind Turbine Generator Drive System with Stochastic Excitation Under Both Displacement and Velocity Delayed Feedback

J. Zhang, Mengran Nan, Lixiang Wei, Xinlei An, Meijuan He
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Abstract

In this paper, a wind turbine generator drive system with stochastic excitation under both displacement and velocity delayed feedback is considered. Firstly, the center manifold method is used to approximate the delay term of the system, so that the Itô-stochastic differential equation can be obtained by random average method. Through the maximal Lyapunov exponential method, the local stochastic stability and random D-bifurcation conditions of the system are obtained. Secondly, it is verified that the increase of noise intensity and delay value induces the occurrence of random P-bifurcation of the system through Monte Carlo numerical simulations. In addition, the theoretical chaos threshold of the system is derived by the random Melnikov method. The results show that the chaos threshold decreases as the noise intensity increases, and the increase in time delay leads to a delay in the chaotic behavior of the system. Finally, the correctness and effectiveness of the chaos-theoretic analysis are verified based on the one-parameter bifurcation diagrams and the two-parameter bifurcation diagrams.
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具有随机激励的风力发电机组驱动系统在位移和速度延迟反馈下的分岔分析
本文研究了一种具有随机激励的风力发电机组驱动系统,该系统同时具有位移和速度延迟反馈。首先,采用中心流形法对系统的延迟项进行近似,利用随机平均法得到Itô-stochastic微分方程;通过极大Lyapunov指数方法,得到了系统的局部随机稳定性和随机d分岔条件。其次,通过蒙特卡罗数值模拟验证了噪声强度和延迟值的增加导致系统随机p分岔的发生。此外,利用随机Melnikov方法推导了系统的理论混沌阈值。结果表明,混沌阈值随噪声强度的增大而减小,而时滞的增大导致系统混沌行为的延迟。最后,基于单参数分岔图和双参数分岔图验证了混沌理论分析的正确性和有效性。
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