4.5 Article

Parameter Identification of ARX Models Based on Modified Momentum Gradient Descent Algorithm

期刊

COMPLEXITY
卷 2020, 期 -, 页码 -

出版社

WILEY-HINDAWI
DOI: 10.1155/2020/9537075

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资金

  1. National Natural Science Foundation of China [61973137]
  2. Fundamental Research Funds for the Central Universities [JUSRP22016]
  3. Funds of the Science and Technology on Near-Surface Detection Laboratory [TCGZ2019A001]

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The parameter estimation problem of the ARX model is studied in this paper. First, some traditional identification algorithms are briefly introduced, and then a new parameter estimation algorithm-the modified momentum gradient descent algorithm-is developed. Two gradient directions with their corresponding step sizes are derived in each iteration. Compared with the traditional parameter identification algorithms, the modified momentum gradient descent algorithm has a faster convergence rate. A simulation example shows that the proposed algorithm is effective.

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