Improved gradient descent algorithms for time-delay rational state-space systems: intelligent search method and momentum method

被引:23
作者
Chen, Jing [1 ]
Zhu, Quanmin [2 ]
Hu, Manfeng [1 ]
Guo, Liuxiao [1 ]
Narayan, Pritesh [2 ]
机构
[1] Jiangnan Univ, Sch Sci, Wuxi 214122, Jiangsu, Peoples R China
[2] Univ West England, Dept Engn Design & Math, Bristol BS16 1QY, Avon, England
基金
中国国家自然科学基金;
关键词
Rational model; Time-delay; Gradient descent; Intelligent search method; Momentum method; PARAMETER-ESTIMATION; MODEL RECOVERY; IDENTIFICATION;
D O I
10.1007/s11071-020-05755-8
中图分类号
TH [机械、仪表工业];
学科分类号
0802 ;
摘要
This study proposes two improved gradient descent parameter estimation algorithms for rational state-space models with time-delay. These two algorithms, based on intelligent search method and momentum method, can simultaneously estimate the time-delay and parameters without the matrix eigenvalue calculation in each iteration. Compared with the traditional gradient descent algorithm, the improved algorithms come with two advantages: having quicker convergence rates and less computational efforts, particularly meaningful for those large-scale systems. A simulated example is selected to illustrate the efficiency of the proposed algorithms.
引用
收藏
页码:361 / 373
页数:13
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