Previous Article in Journal
Analysis of Bubble Flow in an Inclined Tube and Modeling of Flow Prediction
Previous Article in Special Issue
Enhanced Fuzzy-Based Super-Twisting Sliding-Mode Control System for the Cessna Citation X Lateral Motion
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

An Advanced Control Method for Aircraft Carrier Landing of UAV Based on CAPF–NMPC

1
School of Mechanical Engineering, Nanjing University of Science & Technology, Nanjing 210094, China
2
Key Laboratory of Special Engine Technology, Ministry of Education, Nanjing University of Science and Technology, Nanjing 210094, China
*
Author to whom correspondence should be addressed.
Aerospace 2024, 11(8), 656; https://doi.org/10.3390/aerospace11080656 (registering DOI)
Submission received: 23 June 2024 / Revised: 31 July 2024 / Accepted: 8 August 2024 / Published: 11 August 2024
(This article belongs to the Special Issue Flight Control (2nd Edition))

Abstract

This paper investigates a carrier landing controller for unmanned aerial vehicles (UAVs), and a nonlinear model predictive control (NMPC) approach is proposed considering a precise motion control required under dynamic landing platform and environment disturbances. The NMPC controller adopts constraint aware particle filtering (CAPF) to predict deck positions for disturbance compensation and to solve the nonlinear optimization problem, based on a model establishment of carrier motion and wind field. CAPF leverages Monte Carlo sampling to optimally estimate control variables for improved optimization, while utilizing constraint barrier functions to keep particles within a feasible domain. The controller considers constraints such as fuel optimization, control saturation, and flight safety to achieve trajectory control. The advanced control method enhances the solution, estimating optimal control sequences of UAV and forecasting deck positions within a moving visual field, with effective trajectory tracing and higher control accuracy than traditional methods, while significantly reducing single-step computation time. The simulation is carried out using UAV “Silver Fox”, considering several scenarios of different wind scales compared with traditional CAPF–NMPC and the nlmpc method. The results show that the proposed NMPC approach can effectively reduce control chattering, with a landing error in rough marine environments of around 0.08 m, and demonstrate improvements in trajectory tracking capability, constraint performance and computational efficiency.
Keywords: carrier landing; automatic control; particle filter; multiple constraints; nonlinear model predictive control carrier landing; automatic control; particle filter; multiple constraints; nonlinear model predictive control

Share and Cite

MDPI and ACS Style

Chen, D.; Xu, L.; Wang, C. An Advanced Control Method for Aircraft Carrier Landing of UAV Based on CAPF–NMPC. Aerospace 2024, 11, 656. https://doi.org/10.3390/aerospace11080656

AMA Style

Chen D, Xu L, Wang C. An Advanced Control Method for Aircraft Carrier Landing of UAV Based on CAPF–NMPC. Aerospace. 2024; 11(8):656. https://doi.org/10.3390/aerospace11080656

Chicago/Turabian Style

Chen, Danhe, Lingfeng Xu, and Chuangge Wang. 2024. "An Advanced Control Method for Aircraft Carrier Landing of UAV Based on CAPF–NMPC" Aerospace 11, no. 8: 656. https://doi.org/10.3390/aerospace11080656

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Article metric data becomes available approximately 24 hours after publication online.
Back to TopTop