基于移动质量作动的扰动感知机器人滑翔飞艇飞行控制
Disturbance-Aware Flight Control of Robotic Gliding Blimp via Moving Mass Actuation
AI总结：
本文提出基于移动质量作动的扰动感知飞行控制方法，通过MHE-MPC框架提升飞艇在风扰动下的稳定性和控制性能。
摘要：
机器人飞艇作为一种比空气轻的航空系统，具有长航程和固有安全操作的优势，但对风扰动极为敏感。基于最近在移动质量作动方面的进展，本文针对LTA平台缺乏扰动感知控制框架的问题，通过显式建模和补偿风引起的效应来解决。一个移动时间窗口估计器（MHE）推断实时风扰动，并将这些估计提供给模型预测控制器（MPC），从而在风况变化的情况下实现鲁棒的轨迹和航向调节。所提出的方法利用双自由度（2-DoF）移动质量机制，生成惯性力矩和气动力矩以用于姿态和航向控制，从而在易受扰动的环境中提高飞行稳定性。大量在顺风和侧风条件下飞行实验表明，集成的MHE-MPC框架显著优于基准PID控制，证明了其在扰动感知LTA飞行中的有效性。
英文摘要：
Robotic blimps, as lighter-than-air (LTA) aerial systems, offer long endurance and inherently safe operation but remain highly susceptible to wind disturbances. Building on recent advances in moving mass actuation, this paper addresses the lack of disturbance-aware control frameworks for LTA platforms by explicitly modeling and compensating for wind-induced effects. A moving horizon estimator (MHE) infers real-time wind perturbations and provides these estimates to a model predictive controller (MPC), enabling robust trajectory and heading regulation under varying wind conditions. The proposed approach leverages a two-degree-of-freedom (2-DoF) moving-mass mechanism to generate both inertial and aerodynamic moments for attitude and heading control, thereby enhancing flight stability in disturbance-prone environments. Extensive flight experiments under headwind and crosswind conditions show that the integrated MHE-MPC framework significantly outperforms baseline PID control, demonstrating its effectiveness for disturbance-aware LTA flight.
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