Abstract

This paper proposes a multi-stage optimization framework based on iterative second-order cone programming (SOCP) to solve the three-dimensional (3D) multi-point landing guidance (MLG) problem with hazard avoidance. The approach is used to generate the offline optimal trajectories for database construction in Part II of this paper, it aims to select a safe landing point while finding an optimal path to the selected landing point with minimum fuel consumption. First, by introducing binary variables associated with quadratic constraints, the MLG problem with hazard avoidance is equivalently reformulated as a quadratically constrained quadratic programming (QCQP) problem. Next, to solve the reformulated QCQP problem, a multi-stage optimization framework, which is combined with the relaxation technique, is introduced. The proposed method includes two main stages. In the first stage, the reformulated problem is relaxed into a nonconvex QCQP problem via ignoring constraints related to the binary variables, which can be solved by the proposed iterative second-order cone programming (SOCP) with random initial guess. Via solving the relaxed QCQP problem with proposed iterative SOCP, the initial guess for the second phase is generated. In the second phase, with the generated initial guess in the first phase, the proposed iterative SOCP can find the local minimum for the equivalently reformulated QCQP problem. Finally, the effectiveness of the proposed method is verified via numerical simulations.

Department(s)

Mechanical and Aerospace Engineering

Publication Status

Full Access

International Standard Book Number (ISBN)

978-162410699-6

Document Type

Article - Conference proceedings

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2024 American Institute of Aeronautics and Astronautics, All rights reserved.

Publication Date

01 Jan 2023

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