Multi-point powered descent guidance based on optimal sensitivity

Abstract Next-generation powered descent guidance (PDG) for planetary soft landing needs multi-point-guidance capabilities. Multi-point-guidance capabilities involve two parts: landing site selection and trajectory generation. A novel multi-point PDG algorithm is presented in this study. A modified K-means clustering method and optimal sensitivity based on Interior Point OPTimizer (IPOPT) are utilized to select the fuel-optimal landing site from a list of candidate landing sites. The cluster radius is determined by offline calculation. During the selection of the fuel-optimal landing site, estimated trajectories to each candidate landing site are generated by sensitivity analysis. The optimized trajectory to the best landing site can be efficiently obtained based on a good guess of initial value provided by the estimated trajectory. Theoretical error analysis is given for the proposed guidance algorithm. Numerical results indicate that the proposed guidance algorithm can effectively and efficiently address the multi-point powered descent problem.