Identification of closed-loop system by partial least absolute deviation
XU Bao-chang
LIN Zhong-hua
XIAO Yu-yue
Abstract：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(SαS). 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..
Keywords：partial least absolute deviationclosed-loop systemsprincipal component analysiscorrelationimpulse noise
Publication Date：2016-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：9( 1543-1551 )