Adaptive Multiresolution Collocation-Based Sequential Convex Programming for Fuel-Optimal Low-Thrust Transfer Orbit Guidance

doi:10.3390/app16094171

Return

Adaptive Multiresolution Collocation-Based Sequential Convex Programming for Fuel-Optimal Low-Thrust Transfer Orbit Guidance

2026-04-24

DOI：10.3390/app16094171

Original

Original request for help

Save

Abstract

En 中文

The minimum fuel transfer problem in low-thrust trajectory optimization remains a ma-jor challenge and is typically addressed using bang-bang control. A novel methodologyintegrating Adaptive Multiresolution Collocation (AMRC) and Sequential Convex Pro-gramming (SCP) to solve the minimum-fuel low-thrust trajectory optimization problem isproposed. First, the approach employs the cubic spline wavelet-like transform for meshrefinement, where wavelet coefficients serve as error indicators to dynamically concentratenodes in regions of rapid state variation. Then, the nonlinear programming problem is con-vexified via control variable relaxation and small-perturbation linearization, reformulatedas a second-order cone programming (SOCP) problem, and efficiently solved using con-vex optimization tools. Subsequently, progressive selection of the location points ensuresrapid and accurate convergence to the optimal trajectory. Finally, numerical simulationsof Earth-Mars and Earth-Venus transfer validate the effectiveness and accuracy of theAMRC-based method. Compared with conventional approaches, the proposed methodachieves comparable optimality while markedly improving computational efficiency, pre-cisely localizing switching times, and improving numerical precision, requiring only 29.7%of the nodes and 14.7% of the computation time of uniform-grid convex optimization,achieving fuel-optimal deviations within 0.07% of the indirect method and demonstratingaccuracy improvements of 2-3 orders of magnitude over GPOPS.

Keywords:

fuel-optimal

trajectory optimization

multiresolution analysis

wavelet collocation

sequential convex programming