Full-Pose Tracking via Robust Control for Over-Actuated Multirotors

2025-06-19

AI Summary

Over-actuated multirotor UAVs face critical challenges in full-state (position + attitude) trajectory tracking, including infeasible reference commands, sensitivity to external disturbances, and frequent violations of physical actuator constraints. Method: This paper proposes a cascaded robust control architecture. It pioneers the synergistic extension of Incremental Nonlinear Dynamic Inversion (INDI) with structured H∞ control to over-actuated configurations. A geometric guidance-based weighted least-squares control allocation law is designed and formulated as a quadratic program to rigorously enforce actuator saturation limits and torque bounds, ensuring both tracking feasibility and robustness under constraints. Results: Comprehensive simulations on a hexarotor platform demonstrate significant improvements in disturbance rejection and trajectory tracking accuracy. The approach enables execution of complex dynamic maneuvers and exhibits strong potential for real-world engineering deployment.

Technology Category

• Intelligent Robots: State Estimation
• Planning, Routing, and Scheduling: Mixed Discrete/Continuous Planning
• Humans and AI: Planning and Decision Support for Human-Machine Teams

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• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

This paper presents a robust cascaded control architecture for over-actuated multirotors. It extends the Incremental Nonlinear Dynamic Inversion (INDI) control combined with structured H_inf control, initially proposed for under-actuated multirotors, to a broader range of multirotor configurations. To achieve precise and robust attitude and position tracking, we employ a weighted least-squares geometric guidance control allocation method, formulated as a quadratic optimization problem, enabling full-pose tracking. The proposed approach effectively addresses key challenges, such as preventing infeasible pose references and enhancing robustness against disturbances, as well as considering multirotor's actual physical limitations. Numerical simulations with an over-actuated hexacopter validate the method's effectiveness, demonstrating its adaptability to diverse mission scenarios and its potential for real-world aerial applications.

Problem

• Extends INDI and H_inf control to over-actuated multirotors
• Achieves precise full-pose tracking via optimization-based control allocation
• Enhances robustness against disturbances and physical limitations

Innovation

• Robust cascaded control for over-actuated multirotors
• INDI combined with structured H_inf control
• Weighted least-squares geometric guidance allocation