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CLC number: TP399

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2021-08-08

Cited: 0

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Weichao Si

https://orcid.org/0000-0002-5257-7384

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Frontiers of Information Technology & Electronic Engineering  2021 Vol.22 No.9 P.1221-1233

http://doi.org/10.1631/FITEE.2000251


Design and verification of a transfer path optimization method for an aircraft on the aircraft carrier flight deck


Author(s):  Weichao Si, Tao Sun, Chao Song, Jie Zhang

Affiliation(s):  Coastal Defense College, Naval Aviation University, Yantai 264001, China

Corresponding email(s):   luckydevilsi@163.com, luckydevilhan@163.com, sxwxc.1984@163.com, zhangjie9886@126.com

Key Words:  Carrier aircraft, Flight deck, Transfer path planning, KCMPSO algorithm, Method design and validation


Weichao Si, Tao Sun, Chao Song, Jie Zhang. Design and verification of a transfer path optimization method for an aircraft on the aircraft carrier flight deck[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(9): 1221-1233.

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Abstract: 
This paper studies the transfer path planning problem for safe transfer of an aircraft on the aircraft carrier flight deck under a poor visibility condition or at night. First, we analyze the transfer path planning problem for carrier-based aircraft on the flight deck, and define the objective to be optimized and the constraints to be met. Second, to solve this problem, the mathematical support models for the flight deck, carrier aircraft entity, entity extension, entity posture, entity conflict detection, and path smoothing are established, as they provide the necessary basis for transfer path planning of the aircraft on the aircraft carrier. Third, to enable automatic transfer path planning, we design a multi-habitat parallel chaos algorithm (called KCMPSO), and use it as the optimization method for transfer path planning. Finally, we take the Kuznetsov aircraft carrier as a verification example, and conduct simulations. The simulation results show that compared with particle swarm optimization, this method can solve the transfer path planning problem for an aircraft on the aircraft carrier flight deck better.

航母飞行甲板上飞机转运路径优化方法的设计与验证

司维超,孙涛,宋超,张杰
海军航空大学岸防兵学院,中国烟台市,264001
摘要:研究了在能见度较低或夜间情况下,航母飞行甲板上飞机安全转运的路径规划问题。首先,分析了舰载机在飞行甲板上的转运路径规划问题,定义了优化目标和约束条件。其次,为解决这一问题,建立了飞行甲板、舰载机实体、实体扩展、实体姿态、实体冲突检测和路径平滑的数学支持模型,为航母上飞机的转运路径规划提供了必要基础。再次,为实现转运路径自动规划,设计了一种多生境并行混沌算法(KCMPSO),并将其作为转运路径规划的优化方法。最后,以库兹涅佐夫号航空母舰为例进行仿真模拟。仿真结果表明,与粒子群算法相比,该方法能较好解决航母飞行甲板上飞机的转运路径规划问题。

关键词:舰载机;飞行甲板;转运路径规划;KCMPSO算法;方法设计与验证

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Reference

[1]Chen XY, 2018. The U.S. DoD Publish total aviation mishaps in recent years. Int Aviat, 6:25-28.

[2]Hao SQ, Cheng SW, Zhang YP, 2018. A multi-aircraft conflict detection and resolution method for 4-dimensional trajectory-based operation. Chin J Aeronaut, 31(7):1579-1593.

[3]He SH, Yan SW, Xu JW, 2019. Path designing for aircrafts’ taxiing on flight deck while launching. J Nav Aeronaut Astron Univ, 34(1):126-132 (in Chinese).

[4]Helbig M, Engelbrecht AP, 2014. Population-based metaheuristics for continuous boundary-constrained dynamic multi-objective optimisation problems. Swarm Evol Comput, 14:31-47.

[5]Huang C, 2018. Study on Path Planning and Location of Mobile Robot based on Intelligent Optimization Algorithm. MS Thesis, Dalian Jiaotong University, Dalian, China (in Chinese).

[6]Jordehi AR, Jasni J, Wahab NA, et al., 2015. Enhanced leader PSO (ELPSO): a new algorithm for allocating distributed TCSC’s in power systems. Int J Electron Power Energy Syst, 64:771-784.

[7]Liang WJ, 2017. The Research and Implementation of MES based on Hybrid PSO Multi-objective Job Shop Scheduling. MS Thesis, Guangdong University of Technology, Guangzhou, China (in Chinese).

[8]Liu A, Liu K, 2017. Advances in carrier-based aircraft deck operation scheduling. Syst Eng Theory Pract, 37(1):49-60 (in Chinese).

[9]Lu W, 2019. Design and Application of Dynamic Multi-objective Particle Swarm Optimization Algorithm. MS Thesis, Beijing University of Technology, Beijing, China (in Chinese).

[10]Luan TT, 2019. Research on Model and Evaluation Method Capacity for Sortie Process of Carrier Aircraft. MS Thesis, Harbin Engineering University, Harbin, China (in Chinese).

[11]Luo J, Li Y, 2010. Artificial bee colony algorithm with chaotic-search strategy. Contr Dec, 25(12):1913-1916 (in Chinese).

[12]Ma JC, Yao DK, Zhao GH, et al., 2018. Research on airspace planning of tactical training based on discrete particle swarm optimization. Fire Contr Commun Contr, 43(12):94-98 (in Chinese).

[13]Osaba E, Yang XS, Diaz F, et al., 2016. An improved discrete bat algorithm for symmetric and asymmetric traveling salesman problems. Eng Appl Artif Intell, 48:59-71.

[14]Qi C, Wang D, 2016. Dynamic aircraft carrier flight deck task planning based on HTN. IFAC-PapersOnline, 49(12):1608-1613.

[15]Rosli NS, Ibrahim R, Ismail I, 2017. Intelligent prediction system for gas metering system using particle swarm optimization in training neural network. Proc Comput Sci, 105:165-169.

[16]Ryan JC, Banerjee AG, Cummings ML, et al., 2014. Comparing the performance of expert user heuristics and an integer linear program in aircraft carrier deck operations. IEEE Trans Cybern, 44(6):761-773.

[17]Shao Q, 2017. Particle Swarm Optimization and its Application in Engineering. MS Thesis, Jilin University, Jilin, China (in Chinese).

[18]Si WC, Han W, Shi WW, 2012. Research on deck-disposed scheduling method of carrier planes based on PSO algorithm. Acta Aeron Astron Sin, 33(11):2048-2056 (in Chinese).

[19]Si WC, Qi YD, Han W, 2015. Hangar-exporting optimization schedule of multi-carrier plane based on NGA. Fire Contr Commun Contr, 40(11):13-19 (in Chinese).

[20]Song T, 2018. Design and Implementation of Aircraft Landing Information Processing and Display System. MS Thesis, Harbin Engineering University, Harbin, China (in Chinese).

[21]Tian DP, Shi ZZ, 2018. MPSO: modified particle swarm optimization and its applications. Swarm Evol Comput, 41:49-68.

[22]Trelea IC, 2003. The particle swarm optimization algorithm: convergence analysis and parameter selection. Inform Process Lett, 85(6):317-325.

[23]Wu Y, Jin YC, Liu XX, 2015. A directed search strategy for evolutionary dynamic multiobjective optimization. Soft Comput, 19(11):3221-3255.

[24]Yang DS, Wang KF, Chen DW, et al., 2018. Parallel carrier fleets: from digital architectures to smart formations. J Commun Contr, 4(2):101-110 (in Chinese).

[25]Zeng SY, 2017. Aircraft Carrier Deck Task Plan Repair and Replanning Research under Dynamic Environment. MS Thesis, Huazhong University of Science and Technology, Wuhan, China (in Chinese).

[26]Zhao Q, 2019. Analysis and Research on Driving Behavior of Carrier-based Aircraft Tractor. MS Thesis, Shenyang University of Technology, Shenyang, China (in Chinese).

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