Path planning of carrier aircraft traction system based on CL-RRT and MPC

被引：0
|
作者：
Sun J. [1 ]
Yu M. [1 ]
Yang D. [2 ]
Tang H. [2 ]
Bian D. [3 ]
机构：
[1] School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan
[2] China Ship Development and Design Center, Wuhan
[3] The Second Military Representative Office of Naval Equipment Department in Wuhan, Wuhan
来源：
Xi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics | 2024年 / 46卷 / 05期
关键词：
carrier aircraft traction system; close loop rapidly exploring random trees (CL-RRT); model predictive control (MPC); path planning;
D O I：
10.12305/j.issn.1001-506X.2024.05.27
中图分类号：
学科分类号：
摘要：
The transport process of carrier aircraft is difficult because the environment of deck is narrow and complex. A path planning algorithm for the carrier aircraft traction system is proposed combining close loop rapidly exploring random trees (CL-RRT) and model predictive control (MPC). Firstly, the pure pursuit controller and linear quadratic (LQ) controller are used in CL-RRT to obtain the control input of the system, and the planned path is obtained by forward simulation. Secondly, the obtained path is scaled and interpolated as the initial solution of MPC. Finally, the objective function and so on of MPC is set and the final path is solved. The simulation experiment of three customized scenarios is carried out to verify the superiority of the proposed algorithm by comparing with the experimental results of CL-RRT algorithm. Experimental results show that the proposed algorithm can effectively solve the problem of poor solution quality caused by randomness of sampling, and improve the efficiency and safety of carrier aircraft on deck. © 2024 Chinese Institute of Electronics. All rights reserved.
引用
收藏
页码：1745 / 1755
页数：10
相关论文
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