Chai, RunqiSavvaris, AlTsourdos, AntoniosChai, SenchunXia, Yuanqing2018-02-122018-02-122018-01-25Runqi Chai, Al Savvaris, Antonios Tsourdos et. al. Optimal tracking guidance for aeroassisted spacecraft reconnaissance mission based on receding horizon control. IEEE Transactions on Aerospace and Electronic Systems, Volume 54, Issue 4, August 2018, pp1575-15880018-9251http://dx.doi.org/10.1109/TAES.2018.2798219https://dspace.lib.cranfield.ac.uk/handle/1826/12981This paper focuses on the application of model predictive control (MPC) for the spacecraft trajectory tracking problems. The motivation of the use of MPC, also known as receding horizon control, relies on its ability in dealing with control, state and path constraints that naturally arise in practical trajectory planning problems. Two different MPC schemes are constructed to solve the reconnaissance trajectory tracking problem. Since the MPC solves the online optimal control problems at each sampling instant, the computational cost associated with it can be high. In order to decrease the computational demand due to the optimization process, a newly proposed two-nested gradient method is used and embedded in the two MPC schemes. Simulation results are provided to illustrate the effectiveness and feasibility of the two MPC tracking algorithms combined with the improved optimization technique.enAttribution-NonCommercial 4.0 Internationalhttp://creativecommons.org/licenses/by-nc/4.0/Model Predictive Controlspacecraft trajectory trackingreceding horizon controloptimal controltwo-nested gradient methodArticle