Zirui Yu | Searcharxiv

arXiv2026

Robust Distributed Cooperative Path-Following and Local Replanning for Multi-UAVs Under Differentiated Low-Altitude Paths

Multiple fixed-wing unmanned aerial vehicles (multi-UAVs) encounter significant challenges in cooperative path following over complex Digital Elevation Model (DEM) low-altitude airspace, including wind field disturbances, sudden obstacles, and requirements of distributed temporal synchronization during differentiated path tracking. Existing methods lack efficient distributed coordination mechanisms for time-consistent tracking of 3D differentiated paths, fail to quantify robustness against disturbances, and lack effective online obstacle avoidance replanning capabilities. To address these gaps, a cooperative control strategy is proposed: first, the distributed cooperative path-following problem is quantified via time indices, and consistency is ensured through a distributed communication protocol; second, a longitudinal-lateral look-ahead angle adjustment method coupled with a robust guidance law is developed to achieve finite-time stabilization of path following error to zero under wind disturbances; third, an efficient local path replanning method with minimal time cost is designed for real-time online obstacle avoidance.Experimental validations demonstrate the effectiveness and superiority of the $\ $proposed strategy.

cs.RO↗

arXiv2025

Robust Longitudinal-lateral Look-ahead Pursuit Path-Following Control: Fast Finite-Time Stability Guarantee

This paper addresses the challenging problem of robust path-following for fixed-wing unmanned aerial vehicles (UAVs) in complex environments with bounded external disturbances and non-smooth predefined paths. Due to the unique aerodynamic characteristics and flight constraints of fixed-wing UAVs, achieving accurate and fast stable path following remains difficult, especially in low-altitude mountainous terrains, urban landscapes, and under wind disturbances. Most existing path-following guidance laws often struggle to ensure fast stabilization under unknown bounded disturbances while maintaining sufficient robustness, and there is a lack of research on optimizing robustness for non-smooth paths under flight constraints. This paper addresses these issues by proposing a constraints-based robust path-following controller. Firstly, from the perspective of global random attractor, we innovatively introduce robustness metrics that quantify both the exponential convergence rate and the range of the ultimate attractor set. Secondly, building on these metrics, we develop a robust longitudinal-lateral look-ahead pursuit (RLLP) guidance law for fixed-wing UAVs, specifically considering the flight path angle and track angle under external disturbances. Thirdly, we also derive an optimized version (Optimal-RLLP) to enhance the robustness metrics, and elaborate on the sufficient conditions for fast finite-time stability, ensuring the guidance law achieves finite-time stability and robustness with reduced sensitivity to constrained uncertainties. The simulation results validate the proposed guidance law's feasibility, optimality and robustness under atmospheric disturbances using a high-fidelity simulation platform and provide key principle for practical deployment.

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