Latest estimation based recursive stochastic gradient identification algorithms for ARX models

被引:0
作者
Wu, Ai-Guo [1 ]
Fu, Fang-Zhou [1 ]
Teng, Yu [1 ]
机构
[1] Shenzhen Grad Sch Shenzhen, Harbin Inst Technol, Shenzhen 518055, Peoples R China
来源
2015 34TH CHINESE CONTROL CONFERENCE (CCC) | 2015年
关键词
Latest estimation; stochastic gradient; hierarchical identification; SYSTEMS;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A modified recursive stochastic gradient identification algorithm is presented for ARX models. In the presented algorithm, the hierarchical identification principle is first used, and then the unknown true parameters are replaced by their latest estimation. The convergence analysis of the proposed algorithm is given. In addition, a simulation example is employed to show the advantage of the proposed identification algorithms in convergence rates and estimation accuracy compared with some existing algorithms.
引用
收藏
页码:2033 / 2038
页数:6
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