1. Convex–concave optimization for a launch vehicle ascent trajectory with chance constraints.
- Author
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Sun, Xin, Chai, Senchun, Chai, Runqi, Zhang, Baihai, Felicetti, Leonard, and Tsourdos, Antonios
- Subjects
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TRAJECTORY optimization , *DECOMPOSITION method , *NONLINEAR programming , *LAUNCH vehicles (Astronautics) , *NONLINEAR equations , *PROBLEM solving , *COMPUTER software testing - Abstract
The objective of this paper is to present a convex–concave optimization approach for solving the problem of a multistage launch vehicle ascent trajectory. The proposed method combines convex–concave decomposition and successive linearization techniques to generate a new sequence of convex subproblems to replace the original non-convex problem. Bernstein approximation is used to transform the chance constraints into convex ones. A h p -adaptive pseudospectral scheme is employed to discretize the optimal control problem into a nonlinear programming problem with less computation cost. The performance of the proposed strategy is compared against other typical techniques in a selection of test case scenarios. Numerical results demonstrate the viability of the method and show pros and cons of the proposed technique. • A noise-perturbed multi-stage launch vehicle trajectory optimization model is proposed. • The convex–concave decomposition method is applied to the multistage launch vehicle ascent problem. • The convex–concave decomposition and successive linearization methods allow for a reduction of the computational cost. • An extension to handle chance constraints based on Bernstein approximation approach is proposed. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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