Dynamic Identification for Industrial Robot Manipulators Based on Glowworm Optimization Algorithm

被引：7
|
作者：
Ding, Li [1 ]
Shan, Wentao [1 ]
Zhou, Chuan [2 ]
Xi, Wanqiang [3 ]
机构：
[1] Jiangsu Univ Technol, Coll Mech Engn, Changzhou 213001, Peoples R China
[2] Jiangsu Univ Technol, Sch Business, Changzhou 213001, Peoples R China
[3] Nanjing Univ Aeronaut & Astronaut, Coll Mech & Elect Engn, Nanjing 210016, Peoples R China
来源：
INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2017, PT II | 2017年 / 10463卷
关键词：
Industrial robot manipulators; Dynamical identification; Glowworm swarm optimization; Identification experiment; MODEL IDENTIFICATION; PARAMETERS; DESIGN;
D O I：
10.1007/978-3-319-65292-4_68
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Dynamical identification methods for the industrial robot manipulators are widely and successfully applied to obtain a model that is suitable for controller design. In this paper, the dynamical model of robot was obtained by Newton-Euler method and linearized by a particular approach. A novel glowworm swarm optimization algorithm was introduced to estimate the unknown parameters. The algorithm had been coded in the popular Matlab environment and the procedure was tested in a practical case research to identify the dynamical model of a six degree-of-freedom industrial robot. The results of the identification experiment showed the efficiency of the proposed algorithm.
引用
收藏
页码：789 / 799
页数：11
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