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《第36届中国控制会议论文集(B)》2017年
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Coupled Identification Based Approximate Least Absolute Deviation for Multivariable System

Bao-chang Xu  Li-kun Yuan  Hua Zhang  Wei Liu  
【摘要】:Based on approximate least absolute deviation criterion and Newton's search principle, a full coupled identification algorithm is proposed for multivariable system whose model parameters are fully coupled. To solve the non-differentiable problem of the least absolute deviation, an approximate least absolute deviation objective function is established by introducing a deterministic differentiable function to replace the absolute residual. 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(SaS) distribution. Moreover, a differentiable objective function avoids the operation of solving matrix inversion, which makes it easier to calculate. Simulation experiments show that the proposed full coupled identification algorithm can effectively identify the model parameters of multivariable system and restrain the impact of impulse noise.Satisfactory performance and strong robustness indicate the proposed multivariable identification algorithm could be well applied to practical industrial systems.
【作者单位】:Department of Automation,China University of Petroleum(Beijing) CNPC Drilling Engineering Research Institute
【分类号】:N945.14
【正文快照】:
normally distributed(white noise)[8].But when random1 Introductionnoise doesn’t obey the normal distribution,for example,With the development of modern industry,single-variablethere is impulse noise meeting the symmetrical alpha stablesystem can not sat

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