This article addresses the velocity-free attitude control problem for rigid spacecraft with bounded external disturbances. To obtain an accurate estimate of the spacecraft's velocities and external disturbances, a semi-global practical predefined-time extended-state observer is presented in terms of a time-dependent scaling function. Next, a continuous and nonsingular sliding mode surface is designed, and a predefined-time observer is introduced to estimate the derivative of a term in the sliding mode surface. Then, a practical predefined-time velocity-free attitude control scheme is proposed for rigid spacecraft. The developed controller can ensure that the upper limit of the resulting settling time is predefined without dependence on initial conditions or any other parameters. One further salient feature of the present control approach is that a reduced magnitude of the applied control torques is required to achieve satisfactory attitude control performance. Finally, numerical simulation examples are conducted to show the effectiveness of the derived control scheme.

The cooperative positioning problem of hypersonic vehicles regarding LEO constellations is the focus of this research study on space-based early warning systems. A hypersonic vehicle is highly maneuverable, and its trajectory is uncertain. New challenges are posed for the cooperative positioning capability of the constellation. In recent years, breakthroughs in artificial intelligence technology have provided new avenues for collaborative multi-satellite intelligent autonomous decision-making technology. This paper addresses the problem of multi-satellite cooperative geometric positioning for hypersonic glide vehicles (HGVs) by the LEO-constellation-tracking system. To exploit the inherent advantages of hierarchical reinforcement learning in intelligent decision making while satisfying the constraints of cooperative observations, an autonomous intelligent decision-making algorithm for satellites that incorporates a hierarchical proximal policy optimization with random hill climbing (MAPPO-RHC) is designed. On the one hand, hierarchical decision making is used to reduce the solution space; on the other hand, it is used to maximize the global reward and to uniformly distribute satellite resources. The single-satellite local search method improves the capability of the decision-making algorithm to search the solution space based on the decision-making results of the hierarchical proximal policy-optimization algorithm, combining both random hill climbing and heuristic methods. Finally, the MAPPO-RHC algorithm’s coverage and positioning accuracy performance is simulated and analyzed in two different scenarios and compared with four intelligent satellite decision-making algorithms that have been studied in recent years. From the simulation results, the decision-making results of the MAPPO-RHC algorithm can obtain more balanced resource allocations and higher geometric positioning accuracy. Thus, it is concluded that the MAPPO-RHC algorithm provides a feasible solution for the real-time decision-making problem of the LEO constellation early warning system.

A flexible brush mechanism is designed and mounted at the end of a seven-degree-of-freedom robotic arm to despin a tumbling target. The dynamics model of the flexible brush is established using the absolute nodal coordinate method (ANCF), and its contact collision with the solar wing of the tumbling target is analysed. The optimal control is proposed for a seven-degree-of-freedom robotic arm during despinning of a tumbling target while ensuring the global robustness and stability. Simulations verify that the despinning strategy can successfully eliminate the rotation speed and is feasible and effective.

Complex space missions require more space robotic extravehicular operations required to crawl on spacecraft surfaces with discontinuous features at the graspable point, greatly increasing the difficulty of space robot motion manipulation. Therefore, this paper proposes an autonomous planning method for space dobby robots based on dynamic potential fields. This method can realize the autonomous crawling of space dobby robots in discontinuous environments while considering the task objectives and the self-collision problem of robotic arms when crawling. In this method, a hybrid event–time trigger with event triggering as the main trigger is proposed by combining the working characteristics of space dobby robots and improving the gait timing trigger; the dynamic potential field function is designed to adjust the space robot robotic arm grasping point adaptively according to the space robot state. Simulation results verify the effectiveness of the proposed autonomous planning method.

In order to improve the success rate of space debris object capture, how to increase the resistance to interference in the space robot arm has become an issue of interest. In addition, since the space operation time is always limited, finite‐time control has become another urgent requirement needed to be addressed. Considering external disturbances, two control methods are proposed in this paper to solve the control problem of space robot arm. Firstly, a linear sliding mode control method is proposed considering the model uncertainties and external disturbances. The robot arm can track the desired trajectory, while a trade‐off between optimality and robustness of the solved system can be achieved. Then, in order to reduce conservativeness and relax restrictions on external disturbances, a novel backstepping control method based on a finite‐time integral sliding mode disturbance observer is developed, which compensates for the effects of both model uncertainties and infinite energy‐based disturbance inputs. Finally, simulation examples are given to illustrate the effectiveness of the proposed control method.

Extreme cyclic temperature fluctuations (−200 °C to 200 °C) and inherent clearance nonlinearity in deployment hinges severely threaten the on-orbit deployment accuracy and dynamic stability of large variable-geometry spacecraft antennas for geosynchronous Earth orbit applications. However, current modeling approaches suffer from three critical limitations: single-configuration models requiring manual switching, there are inherent geometric nonlinear errors from conventional floating frame formulations, and incomplete thermo-mechanical coupling neglects the temperature effects on contact stiffness and friction. To address these gaps, we propose a unified high-fidelity dynamic model based on the Absolute Nodal Coordinate Formulation (ANCF). This model eliminates geometric errors and mesh mismatch, enables seamless multi-configuration deployment without switching, and fully incorporates temperature-dependent material properties and nonlinear contact forces. An improved Hilber–Hughes–Taylor-$\alpha$ implicit integration algorithm with second-order accuracy and unconditional stability is adopted to solve the strongly nonlinear differential-algebraic equations. Numerical results demonstrate that the proposed model achieves a calculation error below 3% against experimental data, significantly outperforming the traditional floating frame of reference formulation with an error of 15–22%. Non-uniform temperature fields increase thermally induced vibration amplitudes by 32–45%, and every 0.1 increase in the friction coefficient raises the impact force at the clearance hinge by 15–20%. The proposed unified modeling framework provides a solid theoretical basis for deployment stability prediction and the on-orbit control optimization of large variable-geometry spacecraft antennas.