The identification of joint parameters for modular robots using fuzzy theory and a genetic algorithm

Yangmin Li; Xiaoping Liu; Zhaoyang Peng; Yugang Liu

doi:10.1017/S0263574702004277

The identification of joint parameters for modular robots using fuzzy theory and a genetic algorithm

Yangmin Li, Xiaoping Liu, Zhaoyang Peng, Yugang Liu

Research output: Journal article publication › Journal article › Academic research › peer-review

13 Citations (Scopus)

Abstract

This paper discusses a technique for identifying the joint parameters of a modular robot in order to study the dynamic characteristics of the whole structure and to realise dynamic control. A method for identifying the joint parameters of the structure applying fuzzy logic combined with a genetic algorithm has been studied using a 9-DOF modular redundant robot. A Genetic Algorithm was used in the fuzzy optimisation, which helped to avoid converging to locally optimal solutions and made the results identified much more reasonable. The joint parameters of a 9-DOF modular redundant robot have been identified.

Original language	English
Pages (from-to)	509-517
Number of pages	9
Journal	Robotica
Volume	20
Issue number	5
DOIs	https://doi.org/10.1017/S0263574702004277
Publication status	Published - 1 Sept 2002
Externally published	Yes

Keywords

Modal analysis
Modular robots
Parameter identification
Vibration control

ASJC Scopus subject areas

Control and Systems Engineering

More information

10.1017/S0263574702004277

Cite this

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abstract = "This paper discusses a technique for identifying the joint parameters of a modular robot in order to study the dynamic characteristics of the whole structure and to realise dynamic control. A method for identifying the joint parameters of the structure applying fuzzy logic combined with a genetic algorithm has been studied using a 9-DOF modular redundant robot. A Genetic Algorithm was used in the fuzzy optimisation, which helped to avoid converging to locally optimal solutions and made the results identified much more reasonable. The joint parameters of a 9-DOF modular redundant robot have been identified.",

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AB - This paper discusses a technique for identifying the joint parameters of a modular robot in order to study the dynamic characteristics of the whole structure and to realise dynamic control. A method for identifying the joint parameters of the structure applying fuzzy logic combined with a genetic algorithm has been studied using a 9-DOF modular redundant robot. A Genetic Algorithm was used in the fuzzy optimisation, which helped to avoid converging to locally optimal solutions and made the results identified much more reasonable. The joint parameters of a 9-DOF modular redundant robot have been identified.

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KW - Parameter identification

KW - Vibration control

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The identification of joint parameters for modular robots using fuzzy theory and a genetic algorithm

Abstract

Keywords

ASJC Scopus subject areas

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