Distributed Formation Control with Obstacle and Collision Avoidance for Hypersonic Gliding Vehicles Subject to Multiple Constraints

被引:3
作者
Zhang, Zhen [1 ]
Luo, Yifan [1 ]
Qu, Yaohong [1 ]
机构
[1] Northwestern Polytech Univ, Sch Automat, Xian 710129, Shaanxi, Peoples R China
基金
中国国家自然科学基金;
关键词
MODEL-PREDICTIVE CONTROL; PARTICLE SWARM OPTIMIZATION; COOPERATIVE GUIDANCE LAW; REENTRY TRAJECTORY OPTIMIZATION; ENTRY GUIDANCE; SYSTEMS;
D O I
10.1155/2023/9973653
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
Multiple hypersonic gliding vehicles' (HGVs') formation control problems with obstacle and collision avoidance are investigated in this paper, which is addressed in the stage of entry gliding. The originality of this paper stems from the formation control algorithm where constraints of dynamic pressure, heating rate, total aerodynamic load, control inputs, collision avoidance, obstacle avoidance, and the terminal states are considered simultaneously. The algorithm implements a control framework designed to be of two terms: distributed virtual controller and actual control input solver. The distributed virtual controller is based on distributed model predictive control with synchronous update strategy, where the virtual control signals are derived by the optimization simultaneously at each time step for each HGV under directed communication topology. Subsequently, according to the virtual control signals obtained, a coupled nonlinear equation set is solved to get actual control signals: each HGV's bank angle together with the angle of attack. The actual control input solver adopts a feasible solution process to calculate the actual control signals while dealing with constraints. Finally, extensive numerical simulations are implemented to unveil the proposed algorithm's performance and superiority.
引用
收藏
页数:23
相关论文
共 40 条
[1]   Hypersonic Boost-Glide Weapons [J].
Acton, James M. .
SCIENCE & GLOBAL SECURITY, 2015, 23 (03) :191-219
[2]   Data-Driven Based Model-Free Adaptive Optimal Control Method for Hypersonic Morphing Vehicle [J].
Bao, Cunyu ;
Wang, Peng ;
Tang, Guojian .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2023, 59 (04) :3713-3725
[3]   Real-Time Reentry Trajectory Planning of Hypersonic Vehicles: A Two-Step Strategy Incorporating Fuzzy Multiobjective Transcription and Deep Neural Network [J].
Chai, Runqi ;
Tsourdos, Antonios ;
Savvaris, Al ;
Xia, Yuanqing ;
Chai, Senchun .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2020, 67 (08) :6904-6915
[4]   Analytical predictor-corrector entry guidance for hypersonic gliding vehicles [J].
Chen, Huatao ;
Zhao, Kun ;
Guirao, Juan L. G. ;
Cao, Dengqing .
INTERNATIONAL JOURNAL OF NONLINEAR SCIENCES AND NUMERICAL SIMULATION, 2021, 22 (7-8) :955-971
[5]   Multiconstrained Real-Time Entry Guidance Using Deep Neural Networks [J].
Cheng, Lin ;
Jiang, Fanghua ;
Wang, Zhenbo ;
Li, Junfeng .
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, 2021, 57 (01) :325-340
[6]   Nonsingular Sliding Mode Guidance for Impact Time Control [J].
Cho, Dongsoo ;
Kim, H. Jin ;
Tahk, Min-Jea .
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2016, 39 (01) :61-68
[7]   Distributed MPC for formation of multi-agent systems with collision avoidance and obstacle avoidance [J].
Dai, Li ;
Cao, Qun ;
Xia, Yuanqing ;
Gao, Yulong .
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2017, 354 (04) :2068-2085
[8]   Distributed Lyapunov-based model predictive control for collision avoidance of multi-agent formation [J].
Guo, Yaohua ;
Zhou, Jun ;
Liu, Yingying .
IET CONTROL THEORY AND APPLICATIONS, 2018, 12 (18) :2569-2577
[9]   UDE-Based Distributed Formation Control for MSVs with Collision Avoidance and Connectivity Preservation [J].
He, Shude ;
Dai, Shi-Lu ;
Zhao, Zhijia ;
Zou, Tao ;
Ma, Yufei .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2024, 20 (02) :1476-1487
[10]   Distributed Analytical Formation Control and Cooperative Guidance for Gliding Vehicles [J].
Jia, Shengwei ;
Wang, Xiao ;
Li, Fugui ;
Wang, Yulin .
INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING, 2020, 2020