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Optimal path following for small fixed-wing UAVs under wind disturbances

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posted on 2020-03-10, 09:56 authored by Jun Yang, Cunjia LiuCunjia Liu, Matthew CoombesMatthew Coombes, Yunda Yan, Wen-Hua ChenWen-Hua Chen
This paper presents a novel path following algorithm for fixed-wing unmanned aerial vehicles by virtue of a nonlinear optimal control approach and wind disturbance observers. Different from some exiting algorithms, the proposed algorithm formulates the path following problem into a control problem by introducing auxiliary dynamics for the path parameter. The proposed controller is designed in an optimal and systematic manner where the control action is generated according to a well-defined cost function. This framework does not require any complex geometric coordinate transformation and can be easily tuned to accommodate curved reference paths, making it straightforward to deploy in different flight missions. Moreover, the wind influences on the path following performance is explicitly compensated by the proposed algorithm, based on the wind estimates provided by nonlinear disturbance observers. The closed-loop stability, including the auxiliary dynamics for path parameter and observer dynamics for wind estimation, is also analysed. The feasibility and effectiveness of the proposed algorithm have been thoroughly validated in simulation studies and realistic flight tests.

Funding

Autonomous landing of a helicopter at sea: advanced control in adverse conditions (AC2) : EP/P012868/1

National Natural Science Foundation of China (NSFC) under the Grant 6197308

Shenzhen Science and Technology Plan under Grant JCYJ2019081315260359

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Published in

IEEE Transactions on Control Systems Technology

Volume

29

Issue

3

Pages

996-1008

Publisher

IEEE

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by IEEE under the Creative Commons Attribution 4.0 Unported Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/

Acceptance date

2020-03-04

Publication date

2020-04-21

ISSN

1063-6536

eISSN

1558-0865

Language

  • en

Depositor

Dr Cunjia Liu. Deposit date: 9 March 2020

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