引用本文:徐宝昌,林忠华,肖玉月.基于近似偏最小一乘的闭环系统辨识新方法[J].控制理论与应用,2016,33(11):1543~1551.[点击复制]
XU Bao-chang,LIN Zhong-hua,XIAO Yu-yue.Identification of closed-loop system by partial least absolute deviation[J].Control Theory and Technology,2016,33(11):1543~1551.[点击复制]
基于近似偏最小一乘的闭环系统辨识新方法
Identification of closed-loop system by partial least absolute deviation
摘要点击 2793  全文点击 1364  投稿时间:2015-10-31  修订日期:2016-09-09
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DOI编号  10.7641/CTA.2016.50863
  2016,33(11):1543-1551
中文关键词  偏最小一乘  闭环系统  主成分分析  相关性  尖峰噪声
英文关键词  partial least absolute deviation  closed-loop systems  principal component analysis  correlation  impulse noise
基金项目  国家重大科技专项(2011ZX05021–003)资助.
作者单位E-mail
徐宝昌* 中国石油大学北京自动化系 xbcyl@163.com 
林忠华 中国石油大学北京自动化系  
肖玉月 中国石油大学北京自动化系  
中文摘要
      本文基于近似最小一乘准则和主成分分析, 针对反馈通道模型阶次低于前向通道模型阶次且反馈通道不 存在噪声的闭环系统, 进行了近似偏最小一乘递推辨识算法的推导. 为解决最小一乘准则函数不可微的问题, 本文 算法用确定性可导函数近似代替残差绝对值. 近似偏最小一乘辨识算法可以克服基于最小二乘准则的辨识算法在 受到满足(S S)分布的尖峰噪声干扰时残差平方项过大的缺点, 具有目标函数可导, 计算简单的优点. 同时, 通过主 成分分析去除数据向量各元素之间的线性相关, 可以得出模型参数的唯一解. 仿真实验表明, 本文算法可以对反馈 通道模型阶次低于前向通道模型阶次的闭环系统进行直接辨识, 抑制了尖峰噪声对辨识结果的影响, 具有优良的稳 健性, 可以更好地应用于闭环系统辨识.
英文摘要
      Based on approximate least absolute deviation criterion and principal component analysis, a recursive partial approximate least absolute deviation (PALAD) identification algorithm is deduced for closed-loop system whose model order of feedback channel is lower than that of the forward channel and there is no noise in the feedback channel. To solve the non-differentiable problem of the least absolute deviation, a deterministic derivable function is established to approximate the absolute value under certain situations in this paper. The proposed method can overcome the disadvantage of large square residual of least square criterion when the identification data is disturbed by the impulse noise which obeys symmetrical alpha stable distribution(S S). By adopting principal component analysis to eliminate the linear correlation among the elements of data vector, the unique solution of model parameters can be easily acquired by the proposed method. The simulation experiments show that the proposed method can be directly used to identify closed-loop system whose model order of feedback channel is lower than that of the forward channel. Moreover, the proposed algorithm can restrain the impact of impulse noise effectively, has strong robustness and can be better applied to closed-loop identification..