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.

中文翻译：

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基于改进动量梯度下降算法的ARX模型参数辨识

本文研究了ARX模型的参数估计问题。首先简要介绍了一些传统的识别算法，然后开发了一种新的参数估计算法，即改进的动量梯度下降算法。在每次迭代中，将推导出两个梯度方向及其相应的步长。与传统的参数识别算法相比，改进的动量梯度下降算法具有更快的收敛速度。仿真实例表明该算法是有效的。