The Intelligent Trajectory Optimization of Multistage Rocket with Gauss Pseudo-Spectral Method

The rapid developments of artificial intelligence in the last decade are influencing aerospace engineering to a great extent and research this context is proliferating. In paper, trajectory optimization three-stage launch vehicle powering phase subject sun-synchronous orbit considered. To solve optimal control problem, Gauss pseudo-spectral method (GPM) used transform model nonlinear programming (NLP) problem sequential quadratic applied find solution. However, sensitivity initial guess may cost solver significant time do Newton iteration or even lead local minimum. Aiming at issue, good generated by combination harmony search GPM introduced help optimizer faster better (SSO) optimization. Comparative simulation tests conducted with proposed algorithm popular approaches, results indicate that optimized guess, could achieve performance terms convergence ability rate.