Convex optimization for post-fault ascent trajectory replanning using auxiliary phases

Abstract

For ascent trajectory replanning after non-fatal dynamic faults, the terminal orbital constraints and optimization indexes under different replanning strategies usually have very strong nonconvexity, which brings significant challenges to real-time guidance. This paper introduces auxiliary phases to convexify the terminal constraints and objective functions losslessly, significantly improving the convergence and injection accuracy. After lossless and successive convexification, the original problems are converted into a series of convex subproblems. The replanning algorithm is then presented, including the fault detection module, the residual carrying capacity determination module, and the task degradation module. Two typical launch missions are simulated to verify the proposed method's pmethoderformance. Numerical results show that the method can always converge efficiently and reliably in different scenarios and has great potential for real-time onboard applications.