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基于非线性状态空间辨识的气动弹性模型降阶

张家铭 杨执钧 黄锐

张家铭, 杨执钧, 黄锐. 基于非线性状态空间辨识的气动弹性模型降阶[J]. 力学学报, 2020, 52(1): 150-161. doi: 10.6052/0459-1879-19-287
引用本文: 张家铭, 杨执钧, 黄锐. 基于非线性状态空间辨识的气动弹性模型降阶[J]. 力学学报, 2020, 52(1): 150-161. doi: 10.6052/0459-1879-19-287
Zhang Jiaming, Yang Zhijun, Huang Rui. REDUCED-ORDER MODELING FOR AEROELASTIC SYSTEMS VIA NONLINEAR STATE-SPACE IDENTIFICATION[J]. Chinese Journal of Theoretical and Applied Mechanics, 2020, 52(1): 150-161. doi: 10.6052/0459-1879-19-287
Citation: Zhang Jiaming, Yang Zhijun, Huang Rui. REDUCED-ORDER MODELING FOR AEROELASTIC SYSTEMS VIA NONLINEAR STATE-SPACE IDENTIFICATION[J]. Chinese Journal of Theoretical and Applied Mechanics, 2020, 52(1): 150-161. doi: 10.6052/0459-1879-19-287

基于非线性状态空间辨识的气动弹性模型降阶

doi: 10.6052/0459-1879-19-287
基金项目: 1) 国家自然科学基金项目(11972180);机械结构力学及控制国家重点实验室面上项目(MCMS-I-0118G02)
详细信息
    通讯作者:

    黄锐

  • 中图分类号: V211,V215.3

REDUCED-ORDER MODELING FOR AEROELASTIC SYSTEMS VIA NONLINEAR STATE-SPACE IDENTIFICATION

  • 摘要: 高维、非线性气动弹性系统的模型降阶是当前气动弹性力学与控制领域的研究热点之一.然而国内外现有的非线性模型降阶方法仍存在辨识算法复杂、精度有待提高等问题.本研究提出了一种基于非线性状态空间辨识的跨音速气动弹性模型降阶方法. 首先,该方法基于非定常空气动力的单位脉冲响应数据,采用特征系统实现算法对非线性状态空间模型的线性动力学部分进行系统辨识. 其次,引入状态和控制输入的非线性函数, 采用优化算法对非线性函数的系数矩阵进行优化,进而得到考虑非线性效应的空气动力降阶模型.为了验证该降阶模型在预测跨音速气动弹性力学行为的精确性,本文以三维机翼为研究对象,分别从基于非线性降阶模型的气动力辨识、跨声速颤振边界计算和极限环振荡预测三方面进行了算例验证,并与现有的模型降阶方法进行了对比, 进一步说明本文所提出方法的有效性.研究结果表明, 该降阶模型对上述三类问题的计算精度与直接流-固耦合方法相吻合,可用于高效预测飞行器跨声速气动弹性力学行为.

     

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出版历程
  • 收稿日期:  2019-10-17
  • 刊出日期:  2020-02-10

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