Landing Guidance for Reusable Launch Vehicle Using Sequential Convex Programming With Deep Neural Network Based Initialization

被引:1
作者
Kim, Yongho [1 ,2 ]
Park, Yongkyu [2 ]
Choi, Keeyoung [1 ]
机构
[1] Inha Univ, inchenon, South Korea
[2] Korea Aerosp Res Inst, Daejeon, South Korea
关键词
Sequential Convex Programming; Reusable Launch Vehicle; Deep Neural Network;
D O I
10.5139/JKSAS.2023.51.8.507
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
This paper addresses the nonlinear trajectory optimization problem for the landing guidance of vertical takeoff vertical landing reusable launch vehicles, considering translational and rotational constraints. We formulate a 6-degree-of-freedom minimum fuel consumption trajectory optimization problem using dual quaternions and implement onboard sequential convex programming (SCP) with ECOS, a second order cone programming solver. In addition, this paper proposes a deep neural network based method for initial reference trajectory estimation to enhance computation speed of the onboard SCP algorithm. Monte Carlo simulation results show that spline interpolation methods, which more accurately reflect local sharp changes in the initial reference trajectories, outperform polynomial interpolation methods.
引用
收藏
页码:507 / 516
页数:10
相关论文
共 24 条
[1]  
ACIKMESE B, 2013, 23 AAS AIAA SPACE FL
[2]   Convex programming approach to powered descent guidance for Mars landing [J].
Acikmese, Behcet ;
Ploen, Scott R. .
JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 2007, 30 (05) :1353-1366
[3]  
Antsaklis P.J., 2007, A Linear Systems Primer
[4]   Learning-based Warm-Starting for Fast Sequential Convex Programming and Trajectory Optimization [J].
Banerjee, Somrita ;
Lew, Thomas ;
Bonalli, Riccardo ;
Alfaadhel, Abdulaziz ;
Alomar, Ibrahim Abdulaziz ;
Shageer, Hesham M. ;
Pavone, Marco .
2020 IEEE AEROSPACE CONFERENCE (AEROCONF 2020), 2020,
[5]  
Beale M. H., 2023, DEEP LEARNING TOOLBO, P2523
[6]  
Blackmore Lars., 2016, Bridge, V46, P15
[7]  
Boyd SP., 2004, Convex Optimization
[8]  
Domahidi A, 2013, 2013 EUROPEAN CONTROL CONFERENCE (ECC), P3077
[9]  
Grant Michael, 2014, Matlab software for disciplined convex programming
[10]  
Kenright B., 2012, 20 INT C CENTRAL EUR