Aerodynamic Prior-Free Coordinated Trajectory Generation and Tracking Control for a Tail-Sitter UAV

2026-09-10

AI Summary

本文提出一种无需特定气动先验知识的尾座式无人机轨迹生成与跟踪控制框架，通过阶段特异性气动建模策略实现全飞行包线下的精确跟踪。

Abstract

This paper presents a coordinated trajectory generation and tracking control framework for a tail-sitter unmanned aerial vehicle (UAV), which does not require aerodynamic priors identified for a specific airframe while addressing the challenge of flight control under highly nonlinear aerodynamics across the full flight envelope. The core innovation lies in employing phase-specific aerodynamic modeling strategies for planning and tracking, tailored to their distinct functional characteristics, without requiring airframe-specific aerodynamic priors. Specifically, the phi-theory model under coordinated flight is employed to derive an analytic differential flatness mapping, and a simplified but locally accurate model is established for predictive control to enable real-time aerodynamic parameter estimation. The proposed framework is evaluated extensively through both simulation and challenging real-world flight tests under mild wind conditions, showing high-precision tracking and adaptability across the tested aerodynamic conditions. To the best of our knowledge, this is the first real-world demonstration of accurate trajectory tracking over tested flight regimes spanning the full envelope of a tail-sitter UAV without relying on aerodynamic identification campaigns. The source code of our framework is available at: https://github.com/SYSU-HILAB/AP-PnC.

Problem

• coordinated trajectory generation
• tracking control
• tail-sitter UAV
• aerodynamic priors
• nonlinear aerodynamics

Innovation

• aerodynamic prior-free
• phase-specific modeling
• differential flatness
• real-time aerodynamic parameter estimation
• tail-sitter UAV