Robust Control Architecture for Fleet Formation Based on LMI and Artificial Potential Fields

Formation control plays a crucial role in many areas where multiple mobile robots need to be coordinated. In this paper, a formation's control architecture for a homogeneous fleet of three unicycles is proposed. The control architecture is robust by design when using the Linear Matrix Inequality (LMI) based approach. To include collision avoidance into the system, artificial potential fields are inserted in the control algorithm. The closed-loop system performance is evaluated in numerical simulations with different scenarios in motion or still. Simulation results demonstrate that with the proposed controller the agents reach the formation despite the disturbances and, according to the hierarchy defined between them, the unicycles deviate their trajectories to avoid collisions.

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Publication Details

Published
2025-06-08
DOI
https://doi.org/10.1109/sose66311.2025.11083835
Primary Topic
Electric and Hybrid Vehicle Technologies
Type
article
Field-Weighted Citation Impact
0.00
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article

Robust Control Architecture for Fleet Formation Based on LMI and Artificial Potential Fields

Alessandro Bozzi, Enrico Zero, A. Morando, Roberto Sacile et al.
Electric and Hybrid Vehicle Technologies
article

Robust Control Architecture for Fleet Formation Based on LMI and Artificial Potential Fields

Alessandro Bozzi, Enrico Zero, A. Morando, Roberto Sacile, P. Castillo
article en

Abstract

Formation control plays a crucial role in many areas where multiple mobile robots need to be coordinated. In this paper, a formation's control architecture for a homogeneous fleet of three unicycles is proposed. The control architecture is robust by design when using the Linear Matrix Inequality (LMI) based approach. To include collision avoidance into the system, artificial potential fields are inserted in the control algorithm. The closed-loop system performance is evaluated in numerical simulations with different scenarios in motion or still. Simulation results demonstrate that with the proposed controller the agents reach the formation despite the disturbances and, according to the hierarchy defined between them, the unicycles deviate their trajectories to avoid collisions.

Université de Technologie de Compiègne (FR), Centre National de la Recherche Scientifique (FR), Heuristics and Diagnostics for Complex Systems (FR), University of Genoa (IT)
Openalex Percentile: Top 78%
Electric and Hybrid Vehicle Technologies
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