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Optimal path following for small fixed-wing UAVs under wind disturbances
journal contribution
posted on 2020-03-10, 09:56 authored by Jun Yang, Cunjia LiuCunjia Liu, Matthew CoombesMatthew Coombes, Yunda Yan, Wen-Hua ChenWen-Hua ChenThis 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 TechnologyVolume
29Issue
3Pages
996-1008Publisher
IEEEVersion
- VoR (Version of Record)
Rights holder
© The AuthorsPublisher 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
2020-03-04Publication date
2020-04-21ISSN
1063-6536eISSN
1558-0865Publisher version
Language
- en
Depositor
Dr Cunjia Liu. Deposit date: 9 March 2020Usage metrics
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