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一种带有色量测噪声的非线性系统辨识方法

黄玉龙 张勇刚 李宁 赵琳

李娟, 王宇平. 基于样本密度和分类误差率的增量学习矢量量化算法研究. 自动化学报, 2015, 41(6): 1187-1200. doi: 10.16383/j.aas.2015.c140311
引用本文: 黄玉龙, 张勇刚, 李宁, 赵琳. 一种带有色量测噪声的非线性系统辨识方法. 自动化学报, 2015, 41(11): 1877-1892. doi: 10.16383/j.aas.2015.c150278
LI Juan, WANG Yu-Ping. An Incremental Learning Vector Quantization Algorithm Based on Pattern Density and Classification Error Ratio. ACTA AUTOMATICA SINICA, 2015, 41(6): 1187-1200. doi: 10.16383/j.aas.2015.c140311
Citation: HUANG Yu-Long, ZHANG Yong-Gang, LI Ning, ZHAO Lin. An Identification Method for Nonlinear Systems with Colored Measurement Noise. ACTA AUTOMATICA SINICA, 2015, 41(11): 1877-1892. doi: 10.16383/j.aas.2015.c150278

一种带有色量测噪声的非线性系统辨识方法

doi: 10.16383/j.aas.2015.c150278
基金项目: 

国家自然科学基金(61001154,61201409,61371173),中国博士后科学基金(2013M530147,2014T70309),黑龙江省博士后基金(LBH-Z13052,LBH-TZ0505),哈尔滨工程大学中央高校基本科研业务费专项基金(HEUCFQ20150407)资助

详细信息
    作者简介:

    黄玉龙 哈尔滨工程大学自动化学院博士研究生.主要研究方向为惯性导航,滤波算法,组合导航.E-mail:heuedu@163.com

    李宁 哈尔滨工程大学自动化学院副教授.主要研究方向为自适应滤波,组合导航.E-mail:ningli@hrbeu.edu.cn

    赵琳 哈尔滨工程大学自动化学院教授.主要研究方向为惯性导航,卫星导航,组合导航.E-mail:zhaolin@hrbeu.edu.cn

    通讯作者:

    张勇刚 哈尔滨工程大学自动化学院研究员.2007年获得英国Cardiff大学博士学位.主要研究方向为光纤陀螺,惯性导航,滤波算法,组合导航.本文通信作者.E-mail:zhangyg@hrbeu.edu.cn

An Identification Method for Nonlinear Systems with Colored Measurement Noise

Funds: 

Supported by National Natural Science Foundation of China (61001154, 61201409, 61371173), China Postdoctoral Science Foundation (2013M530147, 2014T70309), Heilongjiang Postdoctoral Fund (LBH-Z13052, LBH-TZ0505), and Fundamental Research Funds for the Central Universities of Harbin Engineering University (HEUCFQ20150407)

  • 摘要: 利用最大似然判据, 本文提出了一种带有色量测噪声的非线性系统辨识方法. 首先, 利用量测差分方法将有色量测噪声白色化, 获得新的量测方程, 从而将带有色量测噪声的非线性系统辨识问题转化成带白色量测噪声和一步延迟状态的非线性系统辨识问题. 其次, 利用期望最大化(Expectation maximization, EM)算法提出了一种新的基于最大似然估计的非线性系统辨识方法, 该算法由期望步骤(Expectation step, E-step)和最大化步骤(Maximization step, M-step)两部分组成. 在期望步骤中, 基于当前估计的参数并利用带有色量测噪声的高斯近似滤波器和平滑器, 近似计算完整的对数似然函数的期望. 在最大化步骤中, 近似计算的似然函数期望值被最大化, 并且通过解析更新获得噪声参数估计, 通过Newton更新方法获得模型参数的估计. 最后, 数值仿真验证了本文提出算法的有效性.
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