Parameter identification and vibration control in modular manipulators

Yangmin Li, Yugang Liu, Xiaoping Liu, Zhaoyang Peng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

36 Citations (Scopus)

Abstract

The joint parameters of modular manipulators are prerequisite data for effective dynamic control. A method for identifying these parameters using fuzzy logic was devised to study modular redundant robots. Experimental modal analysis and finite element modeling were exploited to model the dynamics. The joint parameters of a nine degrees-of-freedom (9-DOF) modular robot have been identified. In addition, active vibration control based on a neural network and a genetic algorithm were investigated. Ideal control simulation results for a reduced dynamic model of the 9-DOF modular robot were then derived.
Original languageEnglish
Pages (from-to)700-705
Number of pages6
JournalIEEE/ASME Transactions on Mechatronics
Volume9
Issue number4
DOIs
Publication statusPublished - 1 Dec 2004
Externally publishedYes

Keywords

  • Genetic algorithm
  • Modular robot
  • Neural network
  • Parameter identification
  • Vibration control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Mechanical Engineering

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