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高速列车非线性模型的极大似然辨识

DOI: 10.3724/SP.J.1004.2014.02950, PP. 2950-2958

Keywords: 高速列车,系统辨识,极大似然,平滑滤波器,梯度搜索

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Abstract:

?提出高速列车非线性模型的极大似然(Maximumlikelihood,ML)辨识方法,适合于高速列车在非高斯噪声干扰下的非线性模型的参数估计.首先,构建了描述高速列车单质点力学行为的随机离散非线性状态空间模型,并将高速列车参数的极大似然(ML)估计问题转化为期望极大(Expectationmaximization,EM)的优化问题;然后,给出高速列车状态估计的粒子滤波器和粒子平滑器的设计方法,据此构造列车的条件数学期望,并给出最大化该数学期望的梯度搜索方法,进而得到列车参数的辨识算法,分析了算法的收敛速度;最后,进行了高速列车阻力系数估计的数值对比实验.结果表明,所提出的辨识方法的有效性.

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