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

页码：789 / 799

页数：11

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