Decentralized iterative learning cooperative impedance control for a team of robot manipulators

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations


In this work, we propose a novel decentralized iterative learning cooperative impedance control (ILCIC) framework to cooperatively control the impedance of a robot manipulator team that operates in an iterative manner. Using a novel notion of neighbourhood impedance error, a formation-based architecture based on an undirected communication graph is proposed so that all robots in the team can achieve the desired impedance, even though some robot manipulators may not know the desired angle profiles and their relative configuration with respect to these desired angles. Furthermore, these desired angle profiles and the desired impedance model can be iteration dependent, as the robot manipulator team may need to accomplish different task objectives. Alignment initial conditions are considered, relaxing the identical initial condition (i.i.c.) often considered in the iterative learning control literature which can be restrictive in robotic applications. Through rigourous analysis, it is shown that the impedance error for each robot manipulator converges to zero over the iteration domain, in the sense of LT2 -norm. In the end a simulation example on two 2DOF robot manipulators following a leader robotis presented to demonstrate the efficacy of the proposed framework.

Original languageEnglish
Title of host publicationAdaptive/Intelligent Sys. Control; Driver Assistance/Autonomous Tech.; Control Design Methods; Nonlinear Control; Robotics; Assistive/Rehabilitation Devices; Biomedical/Neural Systems; Building Energy Systems; Connected Vehicle Systems; Control/Estimation of Energy Systems; Control Apps.; Smart Buildings/Microgrids; Education; Human-Robot Systems; Soft Mechatronics/Robotic Components/Systems; Energy/Power Systems; Energy Storage; Estimation/Identification; Vehicle Efficiency/Emissions
ISBN (Electronic)9780791884270
StatePublished - 2020
EventASME 2020 Dynamic Systems and Control Conference, DSCC 2020 - Virtual, Online
Duration: Oct 5 2020Oct 7 2020

Publication series

NameASME 2020 Dynamic Systems and Control Conference, DSCC 2020


ConferenceASME 2020 Dynamic Systems and Control Conference, DSCC 2020
CityVirtual, Online

Bibliographical note

Publisher Copyright:
Copyright © 2020 ASME

ASJC Scopus subject areas

  • Artificial Intelligence
  • Energy Engineering and Power Technology
  • Aerospace Engineering
  • Automotive Engineering
  • Biomedical Engineering
  • Control and Systems Engineering
  • Mechanical Engineering
  • Control and Optimization


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