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Identification algorithm based on the approximate least absolute deviation criteria

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Abstract

Considering the situation that the least-squares (LS) method for system identification has poor robustness and the least absolute deviation (LAD) algorithm is hard to construct, an approximate least absolute deviation (ALAD) algorithm is proposed in this paper. The objective function of ALAD is constructed by introducing a deterministic function to approximate the absolute value function. Based on the function, the recursive equations for parameter identification are derived using Gauss-Newton iterative algorithm without any simplification. This algorithm has advantages of simple calculation and easy implementation, and it has second order convergence speed. Compared with the LS method, the new algorithm has better robustness when disorder and peak noises exist in the measured data. Simulation results show the efficiency of the proposed method.

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Authors and Affiliations

  1. Department of Automation, China University of Petroleum, Beijing, 102249, China

    Bao-Chang Xu & Xin-Le Liu

Authors
  1. Bao-Chang Xu
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  2. Xin-Le Liu
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Corresponding author

Correspondence to Bao-Chang Xu.

Additional information

This work was supported by Important National Science & Technology Specific Projects (No. 2011ZX05021-003)

Bao-Chang Xu graduated from Northeast Petroleum University (NPU), China in 2000. He received his master degree from NPU in 2000, and received his Ph.D. degree from Beijing University of Aeronautics and Astronautics, China in 2005. He is currently an associate professor of control theory and control engineering in China University of Petroleum, Beijing, China.

His research interests include system identification and advanced control, image processing, multisensor data fusion, and soft-sensor technology.

Xin-Le Liu is currently a post graduate student in China University of Petroleum, Beijing, China.

His research interests include intelligent control and system identification.

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Xu, BC., Liu, XL. Identification algorithm based on the approximate least absolute deviation criteria. Int. J. Autom. Comput. 9, 501–505 (2012). https://doi.org/10.1007/s11633-012-0673-x

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  • DOI: https://doi.org/10.1007/s11633-012-0673-x

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