Department of Physical Education, Zhongyuan University of Technology, Zhengzhou, Henan 450007, China.
Comput Intell Neurosci. 2022 May 2;2022:7383074. doi: 10.1155/2022/7383074. eCollection 2022.
Parameter identification is an important branch of automatic control. Due to its special function, it has been widely used in various fields, especially the modeling of complex systems or systems whose parameters are not easy to determine. With the development of control technology, the scale of the control object is getting larger and larger, which makes the calculation amount of the identification algorithm larger and larger. For the nonlinear system with complex structure, especially the nonlinear system containing the product of unknown parameters, the number of parameters of the over-parameterized identification method increases greatly, and the calculation amount of the identification algorithm also increases sharply. Therefore, a parameter estimation method with a small amount of calculation is explored. The results show that the proposed method can overcome the phenomenon of "data saturation", thus improving the parameter identification results.
参数辨识是自动控制的一个重要分支。由于其特殊的功能，已被广泛应用于各个领域，特别是在复杂系统或参数不易确定的系统建模中。随着控制技术的发展，被控对象的规模越来越大，这使得辨识算法的计算量越来越大。对于结构复杂的非线性系统，特别是含有未知参数乘积的非线性系统，过参数化辨识方法的参数数量大大增加，辨识算法的计算量也急剧增加。因此，需要探索一种计算量小的参数估计方法。结果表明，所提出的方法可以克服“数据饱和”现象，从而提高参数辨识的结果。
