Adaptive hierarchical formation control for uncertain Euler–Lagrange systems using distributed inverse dynamics

Muhammad Ridho Rosa, Simone Baldi, Ximan Wang, Maolong Lyu, Wenwu Yu

Research output: Contribution to journalArticleScientificpeer-review

9 Citations (Scopus)

Abstract

This paper establishes a novel adaptive hierarchical formation control method for uncertain heterogeneous nonlinear agents described by Euler–Lagrange (EL) dynamics. Formation control is framed as a synchronization problem where a distributed model reference adaptive control is used to synchronize the EL systems. The idea behind the proposed adaptive formation algorithm is that each agent must converge to the model defined by its hierarchically superior neighbors. Using a distributed inverse dynamics structure, we prove that distributed nonlinear matching conditions between connected agents hold, so that matching gains exist to make the entire formation converge to same homogeneous dynamics: to compensate for the presence of uncertainties, estimation laws are devised for such matching gains, leading to adaptive synchronization. An appropriately designed distributed Lyapunov function is used to derive asymptotic convergence of the synchronization error. The effectiveness of the proposed methodology is supported by simulations of a formation of Unmanned Aerial Vehicles (UAVs).

Original languageEnglish
Pages (from-to)52-65
JournalEuropean Journal of Control
Volume48 ( July 2019)
DOIs
Publication statusPublished - 2018

Keywords

  • Adaptive hierarchical formation control
  • Euler–Lagrange systems
  • Heterogeneous uncertain systems
  • Inverse dynamics control

Fingerprint Dive into the research topics of 'Adaptive hierarchical formation control for uncertain Euler–Lagrange systems using distributed inverse dynamics'. Together they form a unique fingerprint.

Cite this