Robust Model Predictive Control for Aircraft Intent-Aware Collision Avoidance

This paper presents the use of robust model predictive control for the design of an intent-aware collision avoidance system for multi-agent aircraft engaged in horizontal maneuvering scenarios. We assume that information from other agents is accessible in the form of waypoints or destinations. Consequently, we consider that other agents follow their optimal Dubin’s path–a trajectory that connects their current state to their intended state–while accounting for potential uncertainties. We propose using scenario tree model predictive control as a robust approach that demonstrates computational efficiency. We demonstrate that the proposed method can easily integrate intent information and offer a robust scheme that handles different uncertainties. The method is illustrated through simulation results.

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Publication Details

Published
2025-06-24
DOI
https://doi.org/10.23919/ecc65951.2025.11186903
Primary Topic
Advanced Control Systems Optimization
Type
article
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article

Robust Model Predictive Control for Aircraft Intent-Aware Collision Avoidance

Sadegh Soudjani, Sybert Stroeve, Arash Bahari Kordabad, Arabinda Ghosh et al.
Advanced Control Systems Optimization
article

Robust Model Predictive Control for Aircraft Intent-Aware Collision Avoidance

Sadegh Soudjani, Sybert Stroeve, Arash Bahari Kordabad, Arabinda Ghosh, Andrea Da Col
article en

Abstract

This paper presents the use of robust model predictive control for the design of an intent-aware collision avoidance system for multi-agent aircraft engaged in horizontal maneuvering scenarios. We assume that information from other agents is accessible in the form of waypoints or destinations. Consequently, we consider that other agents follow their optimal Dubin’s path–a trajectory that connects their current state to their intended state–while accounting for potential uncertainties. We propose using scenario tree model predictive control as a robust approach that demonstrates computational efficiency. We demonstrate that the proposed method can easily integrate intent information and offer a robust scheme that handles different uncertainties. The method is illustrated through simulation results.

Netherlands Aerospace Centre (NL), Max Planck Institute for Software Systems (DE)
Openalex Percentile: Top 63%
Advanced Control Systems Optimization
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Robust Model Predictive Control for Aircraft Intent-Aware Collision Avoidance — Sadegh Soudjani, Sybert Stroeve, et al. · (2025) | TGRS Research Map | TGRS