An Improved PSO Algorithm for Parameter Identification of Bouc-Wen Model for Piezoelectric Actuator

被引：0
|
作者：
Shao Muyao [1 ]
Huang Jiaqi [1 ]
Wei Shuaihao [1 ]
Gao Zhiyuan [1 ]
机构：
[1] Shanghai Univ, Sch Mechatron Engn & Automat, Shanghai 200444, Peoples R China
来源：
PROCEEDINGS OF THE 39TH CHINESE CONTROL CONFERENCE | 2020年
基金：
中国国家自然科学基金;
关键词：
Particle Swarm Optimization; Parameter Identification; Piezoelectric Actuator; Bouc-Wen Model; FXVSSLMS; Algorithm; PARTICLE SWARM;
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：
An ameliorated particle swarm optimization (APSO) algorithm was proposed in this paper to solve Bouc-Wen model parameter identification problem of piezoelectric actuator. Nonlinear dynamic acceleration coefficients and a modified particle position update approach are employed in PSO to improve the solution accuracy and accelerate the global convergence. Finally, Bouc-Wen model identified by APSO algorithm is experimentally verified on a micro-vibration control experimental platform and can converge to steady-state fast with FXVSSLMS algorithm.
引用
收藏
页码：1070 / 1074
页数：5
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