The identification of space debris’s dynamic parameters is a prerequisite for detumbling and capture operations. In this paper, a novel method for identifying dynamic parameters based on the rope net flexible collision and vision data is proposed, which combines the advantages of full dynamic parameter estimation (contact method) and safety (non-contact method). The point cloud data before and after collision is obtained by LiDAR, and the transformation matrix of point clouds and debris motion data are calculated by point cloud registration. Before the collision, using the motion model-based optimization, the real-time position of the debris center of mass is estimated. And the transformation matrix between visual and debris-fixed coordinates are calculated by the mass center position and transformation matrix of the point cloud. Then, using the debris dynamic model and parameters’ characteristics, the normalized dynamic parameters are estimated. An identification method of net node position changes based on the flexible collision characteristics of rope nets is proposed, which is used to obtain the momentum of the rope net after the collision. Based on the conservation of linear momentum and angular momentum of the satellite-net system, the true values of the mass and the principal moment of inertia of the debris are estimated. The true values of the kinetic energy and momentum can be obtained by substituting the true values of the principal moment of inertia into the normalized parameters, and the full dynamic parameters of large space debris is estimated. Simulations of identifying full dynamic parameters have been performed; the results indicate that this method can provide accurate and real-time true values of dynamic parameters for the detumbling and capture mission.

The space flexible netted pocket capture system provides a flexible and stable solution for capturing non-cooperative space objects. This paper investigates the control problem for the capture of non-cooperative targets undergoing motion. A dynamic model of the capturing net is established based on the absolute nodal coordinate formulation (ANCF) and equivalent plate–shell theory. A contact collision force model is developed using a spring–damper model. Subsequently, a feedforward controller is designed based on the estimated collision force from the dynamic model, aiming to compensate for the collision effects between the target and the net. By incorporating the collision estimation data, an extended state observer is designed, taking into account the collision estimation errors and the flexible uncertainties. A sliding mode feedback controller is then designed using the fast terminal sliding mode control method. Finally, simulation analysis of target capture under different motion states is conducted. The results demonstrate that the spacecraft system’s position and attitude average flutter amplitudes are less than ${10}^{-2}$ m and ${10}^{-2}$ deg. In comparison to standard sliding mode control, the designed controller reduces the attitude jitter amplitude by an order of magnitude, thus demonstrating its effectiveness and superiority.

Most large space debris has large residual angular momentum, and the de-tumbling and capturing operation can easily cause instability and failure of tracking satellites. Therefore, it is necessary to perform real-time dynamic parameter identification of space debris prior to the imminent de-tumbling and capture operation, thus improving the efficiency and success of active debris removal (ADR) missions. A method for identifying dynamic parameters based on the fusion of visual and inertial data is proposed. To obtain the inertial data, the inertial measurement units (IMU) with light markers were fixed on the debris surface by space harpoon, which has been experimentally proven in space, and the binocular vision was placed at the front of a tracking satellite to obtain coordinates of the light markers. A novel method for denoising inertial data is proposed, which will eliminate the interference from the space environment. Furthermore, based on the denoised data and coordinates of the light markers, the mass-center location is estimated. The normalized angular momentum is calculated using the Euler–Poinsot motion characteristics, and all active debris removal parameters are determined. Simulations with Gaussian noise and experiments in the controlled laboratory have been conducted, the results indicate that this method can provide accurate dynamic parameters for the ADR mission.

Existing aerodynamic models of dandelion seeds have treated the filament as rigid or statically prescribed, leaving flexibility-induced wake stabilization unresolved. A three-dimensional partitioned fluid–structure interaction framework coupling large-eddy simulation with an absolute nodal coordinate formulation solver examines compliance at ReD≈470, with additional fixed-compliance cases at ReD=350 and 600. At ReD≈470, Ca=3.06×10−7 retains a centered separated vortex ring and reduces the standard deviation of the resultant transverse-force coefficient by 40.1%, whereas Ca=3.83×10−7 develops late-stage wake inclination and bilateral shedding similar to the rigid case, with the standard deviation reaching 3.0% above the rigid value. At intermediate compliance, azimuthally non-uniform breathing-like motion repositions local passages and is associated with bilaterally balanced leeward low-pressure cores, a reverse-flow centroid offset 19.2% below the rigid value, and weaker transverse velocity gradients, despite little change in the sectional forward-flow partition. Together with the shared low-frequency structural–aerodynamic response, this reorganization characterizes a lower-amplitude coupled state that delays asymmetric shedding, whereas excessive compliance reintroduces wake distortion and transverse-load unsteadiness. The three sampled cases spanning Ca=(2.55−3.06)×10−7 retain at least 99.912% of the rigid mean drag and reduce the transverse-force standard deviation by 40.1%–42.1%. Their longitudinal drag fluctuations increase, but the added standard deviation is only 0.099%–0.160% of the rigid mean drag. At fixed Ca=3.06×10−7, mean drag exhibits an overall decrease broadly consistent with the theoretical ReD−2/3 trend but differs from the corresponding prediction by less than 7.9% over 350≤ReD≤600. The normalized lateral response and force-component trade-off vary with Reynolds number, with pronounced transverse attenuation occurring only at ReD=470 among the sampled conditions.