Midcourse Trajectory Optimization for Variable-flow Ducted Rocket Missiles Based on Convex Optimization컨벡스 최적화 기반의 가변유동형 덕티드 로켓 유도탄의 중기궤적 최적화 연구

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This paper presents a convex optimization-based trajectory optimization method for variable-flow ducted rocket missiles during midcourse engagement to reach the predicted intercept point (PIP). The minimum-intercept time problem is established by reflecting the dynamics and some flight constraints for ducted rocket missiles. An artificial neural network (ANN) is utilized to approximate the nonlinear relationship between several flight conditions and the performance of ducted rockets. In addition, this study, unlike previous studies, proposes selecting the air-to-fuel ratio instead of the fuel mass-flow rate as a control input. This can alter the nonlinear constraint as an equivalent linear constraint by combining it with the pseudospectral method, which is demonstrated in this paper. A convex sub-problem is established by applying successive linearization to the nonlinear dynamic constraint. An improved trust-region algorithm is utilized with the convex sub-problem to solve the original non-convex problem. Numerical optimization results are provided to demonstrate the performance of the proposed method and investigate the optimal trajectory for variable-flow ducted rocket missiles.
Publisher
Institute of Control, Robotics and Systems
Issue Date
2023-08
Language
English
Article Type
Article
Citation

Journal of Institute of Control, Robotics and Systems, v.29, no.8, pp.652 - 661

ISSN
1976-5622
DOI
10.5302/J.ICROS.2023.23.0079
URI
http://hdl.handle.net/10203/314899
Appears in Collection
AE-Journal Papers(저널논문)
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