Abstract：Precise soft rocket recovery landings require precise guidance, navigation, and control. A convex optimization guidance algorithm was developed for soft vertical rocket recovery landings and tested in a closed-loop simulation system. A lossless convex model was combined with successive convex iterations to transform the rocket recovery stage guidance problem into a convex optimization problem using the interior point method. The algorithm robustness was evaluated for various factors including random atmospheric disturbances, engine throttling characteristics, random navigation system deviations, and system delays. The simulations show that the onboard guidance algorithm has millisecond convergence and is very robust. Various simulations show that the closed-loop simulation results can provide precise soft landings for rocket recovery even with the combined effects of various disturbances including dynamic environments, control and navigation system deviations, and system delays.
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