Neural Dynamics for Cooperative Control of Redundant Robot Manipulators

Long Jin, Shuai Li, Xin Luo, Yangming Li, Bin Qin

Research output: Journal article publicationJournal articleAcademic researchpeer-review

93 Citations (Scopus)

Abstract

In this paper, a neural-dynamic distributed scheme is proposed for the cooperative control of multiple redundant manipulators with limited communications. It is guaranteed that, with the communication network being connected, all manipulators can jointly reach the same desired motion. The proposed distributed scheme is rearranged as a time-varying quadratic program and solved online by a Zhang neural network. Then, theoretical analyses show that, without noise, the proposed distributed scheme is able to execute a given task with exponentially convergent position errors. Moreover, an explicit bound relationship between the control input noise and the end-effector position error is analytically derived. Furthermore, numerical comparisons substantiate the superiority, effectiveness, and accuracy of the proposed distributed scheme.

Original languageEnglish
Article number8246544
Pages (from-to)3812-3821
Number of pages10
JournalIEEE Transactions on Industrial Informatics
Volume14
Issue number9
DOIs
Publication statusPublished - 1 Sep 2018

Keywords

  • Distributed control
  • kinematic control
  • redundancy resolution
  • repetitive motion generation
  • Zhang neural network (ZNN)

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Information Systems
  • Computer Science Applications
  • Electrical and Electronic Engineering

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