The large space structure in the assembly process has the characteristics of discrete increment, and its configuration and parameters are constantly change. Different from space structure with fixed configuration, there is currently no in depth research on how to reasonably configure actuators to suppress structural vibration during on orbit assembly process. Hence, the optimal configuration of the actuators in the assembly stage of the large space structure is different from that in the on orbit operation stage. Aiming at the problem, a distributed optimal configuration method of large space structure actuators in the assembly process is proposed in this paper. Considering the characteristics of large space structure which are assembled by modular substructures, the design concept for the actuator distributed optimal configuration in the assembly stage of large space structure is first given. Secondly, the dynamic model of truss structure for actuator placement optimization in assembly process is developed, and the objective function for optimal configuration is developed. The hybrid particle swarm optimization algorithm is improved by combing with the beetle antennae search algorithm; Finally, a numerical example of the position optimization of the actuators of the space smart truss structure in the assembly process is given. The results show that the distributed optimal configuration of actuators in the assembly process of space truss structures is realized by the improved hybrid particle swarm optimization algorithm.

Robot learning algorithms have promoted the development of motion planning and control, and a key issue in robot learning is how to building a high performance robot physics engine. Due to the special environment of spacecrafts, characterized by limited sample data and costly experimental conditions, this paper presents a high fidelity simulation environment for spacecrafts with robot learning algorithms. Adhering to the standard Gym framework, the simulation environment supports a variety of mainstream robot learning algorithm libraries and Gym style control/learning algorithms. Utilizing experimental data from the microgravity simulation system, a data driven approach is employed to construct a spacecraft dynamics model for state updates within the simulation environment. As an illustrative example, the mainstream reinforcement learning algorithm Soft Actor Critic is trained and tested in the constructed simulation environment for the spacecraft stabilization task, demonstrating the feasibility of the simulation environment for robot learning algorithm.

To solve the problem of trajectory tracking control for free floating space manipulator with model uncertainties and external disturbances, a neural network based adaptive sliding mode controller is proposed. To address the model uncertainty, the bidirectional long short term memory neural network (Bi-LSTM) is employed to estimate the uncertainty of the space manipulator model through offline learning. The adaptive sliding mode control is adopted to handle the estimation errors of neural network and external disturbances. The stability of the proposed controller is analyzed via Lyapunov theory. Numerical simulations verify the effectiveness of the proposed control strategy. The results show that the proposed novel controller can effectively improve the control performance at low gains.

Event cameras, a novel type of neuromorphic visual sensor, offer the high temporal resolution and dynamic range, making them suitable for use in computer vision and robotics. This article addresses the challenges of high measurement delay and large data volume in traditional visual systems used in space manipulators by exploring perception and control methods based on event cameras. Asynchronous event stream data generated by event cameras differs from that of traditional cameras, necessitating new algorithms designed specifically for event data. In this paper, a fast circular feature detection and tracking algorithm using iterative reweighting fitting is designed. Building upon this algorithm, a visual servo method adapted to circular features for manipulators is proposed. Experimental results demonstrate that the proposed detection and tracking algorithm achieves a high success rate and significantly faster detection speeds than traditional algorithms. Meanwhile, the event camera’s highspeed feature feedback facilitates more precise servo motion of the manipulators.

The increasing number of space debris has led to frequent collisions among orbiting spacecrafts, posing a huge obstacle to human space exploration. The current distribution of space debris is analyzed with the aim of fewer collision events occurring in areas with dense distribution of space debris. The Density Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm is used to cluster debris based on the fuel consumption required between debris as feature information, and the core objects of debris are determined by the number of neighboring debris that meet the fuel consumption requirements. Satellites that release space vehicles to the vicinity of each debris are selected based on the fuel consumption required, which is equal to the number of clusters. The Hungarian algorithm is used to assign satellite debris cluster clearing tasks, and spacecraft can implement one to many core object clearing tasks in specific clusters.

With the development of space activities in various countries, the number of on orbit failed satellites keeps increasing. To restore the fail satellites as soon as possible, it is necessary to analyze the motion evolution of failed satellites and plan rescue and maintenance tasks both ground based and space based reasonably. However, satellites often carry various types of flexible attachments, and the elastic vibrations of attachments are coupled with the satellite’s attitude and orbital motion. Satellite’s mechanical energy is continuously dissipated since the attachments’ vibration, leading to unique motion evolution characteristics of these satellites from rigid ones. The attitude vibration coupling dynamic model of failed satellites carrying flexible attachments is established to analyze the long term motion evolution convincingly. And the relationship between the energy dissipation and the motion evolution trends is also analyzed. The results show that the initial angular velocity of the satellite, the installation state of flexible attachments, and the structural and material characteristics have a significant impact on the energy dissipation rate, while the initial vibration state of flexible attachments has a small impact on the energy dissipation rate.

In order to achieve efficient and high precision torque calculation, a plasma flow detumbling model based on neural network is established. To address the limitations of traditional guidance laws in handling complex tumbling targets, the principle of nutation stabilization is defined, and an optimal guidance law is designed for plasma flow direction. Simulation results indicate that the rapid dynamics model based on neural network can significantly reduce the torque calculation time while maintaining the same precision. The optimal guidance law can rapidly stabilize complex nutation target. This study significantly improves detumbling efficiency from both onorbit calculation and mission strategy, laying the theoretical foundation for onorbit service based on plasma flow.

The increasing tension in space exposes high orbit satellites to threats from space debris and other spacecrafts. The establishment of a high orbit space based situational awareness system, which enables observation and cataloguing of high orbiting targets, is of great significance to guarantee the normal operation of high orbiting satellites. Optical observation has the advantages of passive passivity, low energy consumption and suitable for long term operation compared with infrared observation. In this paper, the configuration design and coverage analysis of the high orbit optical observation constellation are carried out. A visibility constraint model is established based on the imaging characteristics of the optical load. Target coverage with finite time is established as the optimization index. The configuration optimization design problem is transformed into multiple single satellite optimization problems by decomposition optimization strategy. The differential evolution (DE) algorithm is used for constellation configuration optimal design. The simulation results show that the decomposition optimization strategy has better global optimization characteristics. The relationship between the number of observation satellites and the target coverage is analyzed and the marginal effect of non repetitive target coverage is discussed.

This paper investigates the impulsive control of spacecraft for close proximity approach and maintenance along the sunlight. The concept of approach along the sunlight means that a spacecraft approaches a target, with its position kept on the line connecting the target and the Sun. Firstly, the close proximity relative dynamics is established between the spacecraft and the target. Then the geometrical definition of the sunlight corridor is presented. By transforming the path constraint to the position constraint, a nonlinear programming (NLP) model is developed to describe the optimal impulsive control for the approaching. The time constrained fuel optimal strategy is obtained through solving the NLP model. In addition, the long term variations of the line connecting the target and the Sun are analyzed in the target’s local vertical local horizontal (LVLH) coordinate frame. And an impulsive control strategy is proposed for position maintenance along the sunlight, which is based on the sampling of impulse epochs and positions as well as the dynamical fitting technique. Finally, numerical simulations are conducted to verify the proposed control strategies. The results indicate that the spacecraft can successfully conduct the approach and maintenance, with the sunlight corridor constraint satisfied.

The dynamics of a linear tethered system with three satellites in nontypical plane with orthogonal control force is studied in this paper. An approximate but useful model for a high dimensional nonlinear system is established in the non inertial frame, where three satellites and two space tethers are deemed to be particles and massless springs, respectively. The analytical relationship between the initial state and dynamics and its influence on the critical state of dynamic behavior are derived. A three dimensional dynamic parameter domain is proposed to demonstrate the dynamics in any orbital plane, and verified by numerical simulation. The results show that the analytical calculation is completely consistent with the simulation.