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基于电磁激振的风电叶片双向疲劳加载控制算法研究
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山东省自然科学基金项目(ZR2019MEE076)


Research on Bidirectional Fatigue Loading Control Algorithm of Wind Turbine Blades Based on Electromagnetic Excitation
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    摘要:

    针对双向疲劳加载导致的扰动大且叶片惯性大导致控制难度大、精度达不到要求等问题,提出一种基于电磁力驱动的风电叶片双轴疲劳加载新方法。在对该疲劳加载方法研究的基础上,将具有可调增益的模型参考自适应控制算法应用于风电叶片电磁双轴疲劳加载系统。该算法可根据电磁疲劳加载系统的内部频率变化不断地跟踪参考模型的输出。结合先前研究成果,建立风电叶片电磁力驱动的双轴疲劳加载模型试验平台,在现场试验对自适应算法的控制效果进行验证。结果表明:在挥舞方向,可调增益的模型参考自适应控制算法平均跟踪误差在10%以内,摆振方向为7%以内;相较于传统PID算法,该算法具有更好的跟踪能力、鲁棒性、抗扰动能力,控制性能得到了很大的提升。

    Abstract:

    In view of the problems of disturbance caused by bidirectional fatigue loading and the big control difficulty and inaccuracy caused by big blade inertia,a new method of bidirectional fatigue loading of wind turbine blades based on electromagnetic force was proposed.Based on the research of the fatigue loading method,a new method of double axle fatigue loading of wind turbine blades was proposed.The model reference adaptive control algorithm with adjustable gain was applied to the electromagnetic bidirectional fatigue loading system of the wind turbine blades.By using this algorithm,the output of the reference model could be tracked continuously according to the internal frequency change of the electromagnetic fatigue loading system.Combined with the previous research results,a biaxial fatigue loading model test platform driven by electromagnetic force of wind turbine blades was established,and the control effect of the adaptive algorithm was verified in field test.The results show that in the swing direction,the average tracking error of the reference adaptive control algorithm is within 10% and within 7% in the shimmy direction;compared with the traditional PID algorithm,the proposed algorithm has better tracking ability,better robustness and anti disturbance ability,and the control performance has been greatly improved.

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范治达,张磊安,黄雪梅,叶凯.基于电磁激振的风电叶片双向疲劳加载控制算法研究[J].机床与液压,2022,50(18):118-122.
FAN Zhida, ZHANG Leian, HUANG Xuemei, YE Kai. Research on Bidirectional Fatigue Loading Control Algorithm of Wind Turbine Blades Based on Electromagnetic Excitation[J]. Machine Tool & Hydraulics,2022,50(18):118-122

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  • 在线发布日期: 2023-01-17
  • 出版日期: 2022-09-28