ACTA AERONAUTICAET ASTRONAUTICA SINICA >
Knowledge-based intelligent pigeon-inspired optimization of carrier-based aircraft landing control
Received date: 2024-06-06
Revised date: 2024-07-19
Accepted date: 2024-08-19
Online published: 2024-09-02
Supported by
Liaoning Provincial National Science and Technology Award Project(2022JH25/10200002)
Aiming at the problem of automatic landing of carrier-based aircraft under deck motion and airflow disturbance， a longitudinal landing control law design method based on dynamic inverse control is proposed. The carrier-based aircraft model， deck motion model and stern flow disturbance model are established， and the dynamic inverse control method of carrier-based aircraft landing is designed to estimate the first-order derivative of the reference command within a finite time. An knowledge-based intelligent pigeon-inspired optimization algorithm is proposed to iteratively optimize the parameters of the dynamic inverse controller， which can improve the command following accuracy of carrier-based aircraft landing. The MATLAB Simulink simulation environment is used to simulate and verify the proposed automatic landing control system of carrier-based aircraft. By comparing with pigeon-inspired optimization algorithm and particle swarm optimization algorithm， it is shown that the superiority of the carrier-based aircraft landing control method of knowledge-based intelligent pigeon-inspired optimization， which can significantly improve the accuracy and speed of carrier-based aircraft attitude control， meet the requirements of carrier-based aircraft landing， and has good robustness.
Dapeng ZHOU , Xiaolei QU . Knowledge-based intelligent pigeon-inspired optimization of carrier-based aircraft landing control[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2024 , 45(S1) : 730801 -730801 . DOI: 10.7527/S1000-6893.2024.30801
| 1 | ZHEN Z Y， JIANG S Y， JIANG J. Preview control and particle filtering for automatic carrier landing［J］. IEEE Transactions on Aerospace and Electronic Systems， 2018， 54（6）： 2662-2674. |
| 2 | ASTOLFI A， KARAGIANNIS D， ORTEGA R. Towards applied nonlinear adaptive control［J］. Annual Reviews in Control， 2008， 32（2）： 136-148. |
| 3 | SINGH S， PADHI R. Automatic path planning and control design for autonomous landing of UAVs using dynamic inversion［C］?∥2009 American Control Conference. Piscataway： IEEE Press， 2009： 2409-2414. |
| 4 | ZHENG Z W， JIN Z H， SUN L， et al. Adaptive sliding mode relative motion control for autonomous carrier landing of fixed-wing unmanned aerial vehicles［J］. IEEE Access， 2017， 5： 5556-5565. |
| 5 | SUBRAHMANYAM M B. H-infinity design of F/A-18A automatic carrier landing system［J］. Journal of Guidance， Control， and Dynamics， 1994， 17（1）： 187-191. |
| 6 | LUNGU M H， LUNGU R. Automatic control of aircraft lateral-directional motion during landing using neural networks and radio-technical subsystems［J］. Neurocomputing， 2016， 171： 471-481. |
| 7 | WANG X， CHEN X， WEN L Y. Adaptive disturbance rejection control for automatic carrier landing system［J］. Mathematical Problems in Engineering， 2016， 2016： 7345056. |
| 8 | LUNGU M H. Auto-landing of fixed wing unmanned aerial vehicles using the backstepping control［J］. ISA Transactions， 2019， 95： 194-210. |
| 9 | KOO S， KIM S， SUK J， et al. Improvement of shipboard landing performance of fixed-wing UAV using model predictive control［J］. International Journal of Control， Automation and Systems， 2018， 16（6）： 2697-2708. |
| 10 | LUNGU M H. Auto-landing of UAVs with variable centre of mass using the backstepping and dynamic inversion control［J］. Aerospace Science and Technology， 2020， 103： 105912. |
| 11 | ZHEN Z Y， JIANG S Y， MA K. Automatic carrier landing control for unmanned aerial vehicles based on preview control and particle filtering［J］. Aerospace Science and Technology， 2018， 81： 99-107. |
| 12 | DUAN H B， HUO M Z， YANG Z Y， et al. Predator-prey pigeon-inspired optimization for UAV ALS longitudinal parameters tuning［J］. IEEE Transactions on Aerospace and Electronic Systems， 2019， 55（5）： 2347-2358. |
| 13 | YANG Z Y， DUAN H B， FAN Y M， et al. Automatic carrier landing system multilayer parameter design based on Cauchy mutation pigeon-inspired optimization［J］. Aerospace Science and Technology， 2018， 79： 518-530. |
| 14 | DENG Y M， DUAN H B. Control parameter design for automatic carrier landing system via pigeon-inspired optimization［J］. Nonlinear Dynamics， 2016， 85（1）： 97-106. |
| 15 | DUAN H B， QIAO P X. Pigeon-inspired optimization： A new swarm intelligence optimizer for air robot path planning［J］. International Journal of Intelligent Computing and Cybernetics， 2014， 7（1）： 24-37. |
| 16 | XU X B， DENG Y M. UAV power component-DC brushless motor design with merging adjacent-disturbances and integrated-dispatching pigeon-inspired optimization［J］. IEEE Transactions on Magnetics， 2018， 54（8）： 7402307. |
| 17 | ZHANG B， DUAN H B. Three-dimensional path planning for uninhabited combat aerial vehicle based on predator-prey pigeon-inspired optimization in dynamic environment［J］. IEEE/ACM Transactions on Computational Biology and Bioinformatics， 2017， 14（1）： 97-107. |
| 18 | DUAN H B， WANG X H. Echo state networks with orthogonal pigeon-inspired optimization for image restoration［J］. IEEE Transactions on Neural Networks and Learning Systems， 2016， 27（11）： 2413-2425. |
| 19 | DUAN H B， HUO M Z， SHI Y H. Limit-cycle-based mutant multiobjective pigeon-inspired optimization［J］. IEEE Transactions on Evolutionary Computation， 2020， 24（5）： 948-959. |
| 20 | DUAN H B， CHEN L， ZENG Z G. Automatic landing for carrier-based aircraft under the conditions of deck motion and carrier airwake disturbances［J］. IEEE Transactions on Aerospace and Electronic Systems， 2022， 58（6）： 5276-5291. |
| 21 | DUAN H B， YUAN Y， ZENG Z G. Automatic carrier landing system with fixed time control［J］. IEEE Transactions on Aerospace and Electronic Systems， 2022， 58（4）： 3586-3600. |
/
| 〈 |
|
〉 |
CJA