Mapped Chebyshev Pseudospectral Convex Optimization for Martian Ascent Trajectory Planning

Mapped Chebyshev pseudospectral convex optimization approach was proposed for Martian ascent trajectory optimization. Firstly, the lossless convexification technique was used to convexify the fuel-optimal problem of Martian ascent. Then, the convexified problem was discretized at mapped Chebyshev-Gauss-Lobatto points and interpolated by the barycentric rational interpolation techniques. Finally, the sequential convex optimization method was used to solve the convex problem iteratively to obtain the numerical optimal solution. Simulation results show that the proposed method is superior to the classical sequential convex optimization method in computational efficiency, and effectively improves the ill-condition of standard Chebyshev differential matrices.