Distributed formation control of networked mechanical systems

Journal article (2022)

Authors

N. Javanmardi University of Tehran
L.P. Borja Rosales Learning & Autonomous Control - Mechanical, Maritime and Materials Engineering
M. J. Yazdanpanah University of Tehran
J.M.A. Scherpen Support Delft Center for Systems and Control - Mechanical, Maritime and Materials Engineering , University Medical Center Groningen
Research Group
Learning & Autonomous Control (Mechanical, Maritime and Materials Engineering) (TU Delft)
Copyright: © 2022 N. Javanmardi, L.P. Borja Rosales, M. J. Yazdanpanah, J.M.A. Scherpen
DOI: https://doi.org/10.1016/j.ifacol.2022.07.275
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Published Date

2022

Language

English

Faculty

Mechanical, Maritime and Materials Engineering

Department

Cognitive Robotics

Research Group

Learning & Autonomous Control

Abstract

This paper investigates a distributed formation tracking control law for large-scale networks of mechanical systems. In particular, the formation network is represented by a directed communication graph with leaders and followers, where each agent is described as a port-Hamiltonian system with a constant mass matrix. Moreover, we adopt a distributed parameter approach to prove the scalable asymptotic stability of the network formation, i.e., the scalability with respect to the network size and the specific formation preservation. A simulation case illustrates the effectiveness of the proposed control approach.