This paper presents a new method for rapid generation of time-optimal trajectories for asteroid landing via convex optimization. To overcome the nonconvex difficulty due to the free-flight time, a minimum-landing-error problem that can be convexified is proposed to serve as a gateway for solving the time-optimal control problem. The proposed method solves the reduced minimum-landing-error problem via convex optimization first and then searches for the minimum flight time through a combination of extrapolation and bisection methods. The effectiveness of the proposed methodology for rapidly generating time-optimal trajectories is validated through simulations of spacecraft landing on two asteroids with both finite thrust and low thrust.

The fuel-optimal control problem of soft landing becomes a significant challenge due to the highly irregular gravitational field of an asteroid. An indirect method is used to deal with this fuel-optimal control problem. The difficult bang-bang control problem caused by the indirect method is solved through an improved fast homotopic approach. To validate the advanced homotopic method, the landing site is selected in a region where the gravitational field is especially irregular. The results show that this method is effective for the fuel-optimal control problem in an irregular gravitational field. Moreover, the trajectory designed with the fuel-optimal control is taken as a nominal descent trajectory for a sliding mode control. Monte Carlo simulations show that the desired soft landing can be achieved by tracking the fuel-optimal trajectory.

This Paper presents a fast homotopy method for solving fuel-optimal asteroid landing trajectories. Similar to the traditional homotopy method, the fuel-optimal control problem is connected with the...

This paper investigates the satellite constellation scheduling problem for non-cooperative space object tracking. Different from the traditional earth observation tasks, space object tracking tasks require observation of fast moving targets that may have unpredictable trajectories, and estimation of the position of the targets through cooperative observation of multiple satellites. An agent-based scheduling framework is proposed to enable real-time, distributed scheduling of LEO constellation satellites for tracking non-cooperative space targets. In the proposed framework, a non-linear filtering of the targets’ trajectories is incorporated, and the observation satellites are dynamically allocated according to the status of the satellites and the states of the non-cooperative targets. Specifically, event triggers of tracking space targets for activating task handover among satellites are defined and classified into five categories. The event-trigger processing and task response mechanism are embedded in the proposed scheduling framework. Thereafter, autonomously adjusting the observation-satellite sets can be achieved through distributed negotiation within only a few satellites. The effectiveness of the proposed method is validated by simulating scenarios of tracking targets without or with maneuvers.