Abstract
A novel sequential convex (SCvx) optimization scheme via the Chebyshev pseudospectral method is proposed for efficiently solving the hypersonic reentry trajectory optimization problem which is highly constrained by heat flux, dynamic pressure, normal load, and multiple no-fly zones. The Chebyshev-Gauss Legend (CGL) node points are used to transcribe the original dynamic constraint into algebraic equality constraint; therefore, a nonlinear programming (NLP) problem is concave and time-consuming to be solved. The iterative linearization and convexification techniques are proposed to convert the concave constraints into convex constraints; therefore, a sequential convex programming problem can be efficiently solved by convex algorithms. Numerical results and a comparison study reveal that the proposed method is efficient and effective to solve the problem of reentry trajectory optimization with multiple constraints.
Highlights
The trajectory optimization problem for a hypersonic vehicle constrained by heat rating, dynamic pressure, normal load, and other constraints related to the specified mission is often a highly constrained nonlinear dynamic programming problem which, in general, can be solved by two types of methods: direct and indirect methods [1]
In [10], an sequential convex (SCvx) optimization framework is proposed for solving nonconvex optimal control problems, in which the concave inequality constraint is successively approximated by linearization on the iterated solution rendering a International Journal of Aerospace Engineering convex optimization problem suited to be solved by second-order conic programming (SOCP) algorithms
We develop a new SCvx optimization algorithm based on the Chebyshev pseudospectral method to improve the SCvx optimization method proposed in our previous work [7], in which the dynamic programming problem of reentry trajectory optimization is transcribed into a nonlinear programming problem by using the equispace discretizing technique, and the convexification method and SCvx algorithm are employed to efficiently obtain the optimal trajectory
Summary
The trajectory optimization problem for a hypersonic vehicle constrained by heat rating, dynamic pressure, normal load, and other constraints related to the specified mission is often a highly constrained nonlinear dynamic programming problem which, in general, can be solved by two types of methods: direct and indirect methods [1]. In [10], an SCvx optimization framework is proposed for solving nonconvex optimal control problems, in which the concave inequality constraint is successively approximated by linearization on the iterated solution rendering a International Journal of Aerospace Engineering convex optimization problem suited to be solved by SOCP algorithms. This convex optimization method has been successfully used for addressing trajectory optimization problems of hypersonic vehicles [11].
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