An Online Data-Driven Method for Accurate Detection of Thermal Updrafts Using SINDy

An Online Data-Driven Method for Accurate Detection of Thermal Updrafts Using SINDy

Utilizing thermal updrafts shows potential for enabling long-endurance cruising of fixed-wing unmanned aerial vehicles without energy consumption. This article presents a novel online method based on sparse identification of nonlinear dynamics (SINDy) approach to achievement identification of therma...

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Bibliographic Details
Main Authors: Yufeng Lu, Chenglou Liu, Haichao Hong, Yunwei Huang, Tingwei Ji, Fangfang Xie
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Aerospace
Subjects:
autonomous soaring
static soaring
parameter identification
energy harvesting
thermal updraft
long-endurance glider
Online Access:https://www.mdpi.com/2226-4310/11/10/858
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Summary:Utilizing thermal updrafts shows potential for enabling long-endurance cruising of fixed-wing unmanned aerial vehicles without energy consumption. This article presents a novel online method based on sparse identification of nonlinear dynamics (SINDy) approach to achievement identification of thermal sources in the atmosphere. Initially, the algorithm is incorporated into the upper-level planning system, interacting with the lower-level controller. Then, experiments are conducted through software-in-the-loop simulations (SITL) to validate the implementation of the proposed algorithm. It is found that direct observation of thermal sources through measurements using SINDy is unfeasible during straight and circular flight modes. Nevertheless, simulation analysis of the proposed approach indicates that under unobservable conditions, a portion of the parameters can still be identified. By comparing results obtained using the particle filter algorithm, this method is shown to accurately estimate the parameters with negligible errors under observability conditions. The novelty of this approach lies in its significant improvement of the localization accuracy of the thermal source, without the need for parameter adjustments in the algorithm. Finally, the proposed methods are integrated into commonly used hardware platforms, and their online feasibility is verified through hardware-in-the-loop simulations.
ISSN:2226-4310

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