ROSYOCJun 28, 2020

Quaternion Feedback Based Autonomous Control of a Quadcopter UAV with Thrust Vectoring Rotors

arXiv:2006.15686v118 citations
Originality Incremental advance
AI Analysis

This work addresses control challenges for a novel type of UAV with tilt-motion rotors, offering a method for stable hovering during large maneuvers, but it is incremental as it builds on existing quaternion and control allocation techniques.

The authors tackled the problem of autonomous flight control for an over-actuated quadcopter with thrust vectoring rotors, using quaternion feedback to avoid singularities and simplify state estimation, achieving stable performance in simulations for attitude tracking and way-point navigation.

In this paper, we present an autonomous flight controller for a quadcopter with thrust vectoring capabilities. This UAV falls in the category of multirotors with tilt-motion enabled rotors. Since the vehicle considered is over-actuated in nature, the dynamics and control allocation have to be analysed carefully. Moreover, the possibility of hovering at large attitude maneuvers of this novel vehicle requires singularity-free attitude control. Hence, quaternion state feedback is utilized to compute the control commands for the UAV motors while avoiding the gimbal lock condition experienced by Euler angle based controllers. The quaternion implementation also reduces the overall complexity of state estimation due to absence of trigonometric parameters. The quadcopter dynamic model and state space is utilized to design the attitude controller and control allocation for the UAV. The control allocation, in particular, is derived by linearizing the system about hover condition. This mathematical method renders the control allocation more accurate than existing approaches. Lyapunov stability analysis of the attitude controller is shown to prove global stability. The quaternion feedback attitude controller is commanded by an outer position controller loop which generates rotor-tilt and desired quaternions commands for the system. The performance of the UAV is evaluated by numerical simulations for tracking attitude step commands and for following a way-point navigation mission.

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