Jie Wang

Designing time-optimal trajectories for solar sail spacecraft is highly difficult due to the strong nonlinearity of the solar radiation pressure model, the attitude–orbit coupling, and the prevalence of local minima, which often lead to the failure of gradient-based solvers lacking adequate initial guesses. To address this issue, the present study proposes a two-stage hybrid optimization framework: a coarse-search stage uses B-spline-parameterized metaheuristics to identify a dynamically feasible trajectory, which then serves as a physics-informed warm start for direct-collocation-based gradient refinement, strictly satisfying the full nonlinear dynamics and terminal constraints. The methodology is validated through three increasingly difficult space missions: a rendezvous between Earth and Mars (Case A), a near-Earth asteroid rendezvous considering non-ideal optical reflection (Case B), and a Solar Polar Orbiter mission necessitating an 82.75° inclination adjustment with a thermal safety constraint (Case C). Statistical evaluations reveal that no single metaheuristic dominates universally; each algorithm’s suitability is contingent on the problem’s constraint structure. The hybrid framework further shows a consistent advantage over stand-alone direct collocation: by redirecting the gradient solver toward favorable convergence basins, it locates transfer solutions that remain inaccessible from a cold start.

A solar sail is a spacecraft propulsion system that uses the pressure of light to push a spacecraft. It consists of a lightweight support structure that deploys a large area of flexible film. During attitude maneuvering in space, the solar sail will excite vibrations in the flexible support structure and film, which can affect the accuracy of the attitude control system. To address this issue, this article first establishes a rigid-flexible coupled dynamic model of the solar sail that includes attitude motion and flexible structure elastic vibrations. Then, based on an adaptive sliding mode control method, a solar sail attitude maneuvering method is proposed. Finally, a numerical simulation is conducted using a hexagonal-shaped solar sail as the object. The numerical simulation results show that the attitude maneuvering method has the performance of attitude tracking and attitude stabilization, can meet the requirements of large-angle attitude maneuvering for solar sail spacecraft, and has strong robustness to model parameter uncertainty.

The authors of this paper propose a robust star identification algorithm for a ‘Lost-In-Space’-mode star tracker for lost-cost CubeSat missions. A two-step identification framework and an embedded validation mechanism were designed to accelerate the process. In the first step, a masked distance map is designed to provide a shortlist of stars, and the embedded fast validation process enables the direct output of validated stars before the second step. In the second step, local similarity is utilized to select a set of stars from those shortlisted, and the final validation procedure rejects all unsatisfactory stars. This algorithm can provide reliable and robust recognition even when the captured star images include severe star positioning errors, missing stars and false stars. The proposed algorithm was verified by a simulation study under various conditions. As low-cost star sensors face harsh and unknown environments during deep space CubeSat missions such as asteroid exploration, the proposed algorithm with high robustness will provide an important function.

Conducting a wrinkling analysis for a membrane structure of complex boundary conditions is quite difficult. This paper develops a numerical calculation method for completing a wrinkling analysis of a square membrane structure and a trapezoidal membrane structure with static corner forces. Furthermore, an experimental system for measuring the wrinkle is designed and established to verify the correctness of the method. The difference between simulation analysis results and experimental results is quite small for small corner forces, which means the method used for the wrinkling analysis under small loads is effective.

This paper proposes a modified glideslope guidance method that optimizes a hybrid multiobjective of bearing-only navigation error and fuel consumption. The traditional glideslope guidance fixes uniform maneuver intervals and the initial approach velocity as a predetermined value, making this approach inflexible. In this paper, the maneuver intervals and the initial approach velocity were used as optimization variables, and a hybrid cost function was designed. The tradeoff between the two objectives was analyzed with a bearing-only navigation simulation conducted to reveal the navigation performance following different resulting trajectories. The result showed that the optimal scheduled times of maneuvers remained relatively stable under different tradeoff weights, while a strong correlation between the optimal initial approach velocity and the tradeoff weight was revealed. Therefore, when the optimization has to be solved several times online with different tradeoff weights, the initial approach velocity can be the only optimization variable, leaving the scheduled times of maneuvers fixed in the optimal values achieved offline. These findings provide a potential reference for far-approach trajectory design of bearing-only navigation.