Disturbance-Aware Flight Control of Robotic Gliding Blimp via Moving Mass Actuation

2026-01-29

AI Summary

This study addresses the challenge of wind disturbance susceptibility in lighter-than-air airships, which often lack effective disturbance rejection control strategies. To this end, the authors propose a real-time wind disturbance compensation framework that integrates a moving-mass actuation mechanism with disturbance-aware control. Specifically, a two-degree-of-freedom moving mass generates both inertial and aerodynamic moments, while a moving horizon estimator (MHE) provides online estimation of wind disturbances. These estimates are then fed into a model predictive controller (MPC) to achieve robust trajectory and heading regulation. This work presents the first coordinated integration of moving-mass actuation with joint disturbance estimation and predictive control, significantly enhancing airship stability in complex wind environments. Experimental results demonstrate superior control performance over conventional PID methods under both headwind and crosswind conditions.

Technology Category

• Planning, Routing, and Scheduling: Replanning and Plan Repair
• Intelligent Robots: State Estimation
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

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.

Problem

• disturbance-aware control
• wind disturbance
• lighter-than-air systems
• flight stability
• robust trajectory regulation

Innovation

• moving mass actuation
• disturbance-aware control
• model predictive control
• moving horizon estimation
• lighter-than-air vehicle