PowerLine Unmanned Surfer (PLUS): Shape Adaptive Dynamics Development and Control Design

TL;DR

This paper presents a shape-adaptive UAV design that can harvest energy from power lines and precisely track powerline contours using a frequency-matching control approach, enhancing endurance and tracking accuracy.

Contribution

It introduces a novel shape-adaptive UAV control framework for powerline tracking and energy harvesting, with a frequency-matching approach for improved precision.

Findings

34% of powerline segments tracked with less than 1m error

Shape adaptation improves tracking accuracy and energy harvesting

Wingspan and chord significantly affect tracking performance

Abstract

This paper introduces the powerline unmanned surfer (PLUS) concept to extend the limited endurance of fixed wing unmanned aerial vehicles (UAVs) via in-flight energy harvesting from overhead electrical distribution power lines, and develops the flight dynamics and control framework to support centimeter-scale longitudinal powerline frequency tracking. The dynamics framework models the UAV's shape adaptive structure, aerodynamic forces, and control inputs, and applies the coupled flight mechanics framework to low clearance tracking of powerline contours. This study develops a "trajectory to shape-adaptive UAV" controller design approach for longitudinal powerline tracking through local spatial frequency matching. The frequency-matching approach dynamically regulates the aircraft modes' frequency to the powerline catenary spatial frequency using a generalized parameter linearization approach. Performance is assessed on an example UAV implementing camber and thickness morphing by quantifying clearance distance from neighborhood to high voltage powerline environments and across span and chord combinations. This approach achieves alternating periods of low-clearance tracking and antiphase oscillation, with 34% of the powerline having tracking error less than 1m. Airfoil thickness increase has a stronger effect over Phugoid mode wavelength than thickness decrease. Wingspan, chord, and powerline parameter sensitivities are quantified, providing a foundation for near-field long-distance powerline tracking and energy harvesting.