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Consensus in networks of uncertain robot manipulators without using neighbors’ velocity information

Published online by Cambridge University Press:  30 June 2021

Seyed Mostafa Almodarresi*
Affiliation:
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan84156-83111, Iran
Marzieh Kamali
Affiliation:
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan84156-83111, Iran
Farid Sheikholeslam
Affiliation:
Department of Electrical and Computer Engineering, Isfahan University of Technology, Isfahan84156-83111, Iran
*
*Corresponding author. Email: almodarresi8@gmail.com

Abstract

In this paper, new distributed adaptive methods are proposed for solving both leaderless and leader–follower consensus problems in networks of uncertain robot manipulators, by estimating only the gravitational torque forces. Comparing with the existing adaptive methods, which require the estimation of the whole dynamics, presented methods reduce the excitation levels required for efficient parameter search, the convergence time, and the complexity of the regressor. Additionally, proposed schemes eliminate the need for velocity information exchange between the agents. Global asymptotic synchronization is shown by introducing new Lyapunov functions. Simulation results are provided for a network of 10 4-DOF robot manipulators.

Type
Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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