In multisatellite cooperative missions for space-target observation, the concurrent execution of observation and inter-satellite laser communication imposes stringent requirements on system dynamic performance. Because of the strong coupling between satellite attitude motion and two-axis gimbal dynamics, conventional decoupled control strategies are inadequate for ensuring both target-tracking accuracy and communication-link stability. To address this issue, an integrated attitude dynamics model is established and a fast terminal sliding-mode adaptive controller is proposed. The integrated model, derived from d’Alembert’s principle, characterizes the strong dynamic coupling between the satellite and the two-axis gimbals. The proposed controller combines the minimum learning parameter algorithm with a radial basis function neural network to estimate and compensate for the upper bound of an integrated disturbance term, thus realizing robust control with low computational complexity. The accuracy and feasibility of the proposed model and controller were evaluated through numerical simulations. Furthermore, a comprehensive performance comparison among the proposed controller and three comparison controllers was conducted, demonstrating that the proposed method achieves faster convergence and smaller steady-state errors.

This paper proposes a structure-preserving zero-vibration-derivative (ZVD) input shaping method for fully actuated flexible spacecraft to achieve simultaneous high-precision attitude control and multi-modal vibration suppression. Conventional torque-shaping approaches, when directly applied to control inputs, may degrade attitude precision due to the disruption of the fully actuated system structure. To overcome this issue, we propose a virtual input-based zero-vibration-derivative (ZVD) torque shaping method, in which the ZVD filter is applied to the virtual linearized control input rather than directly to the actual torque. Simulation results demonstrate that the proposed method effectively suppresses flexible vibrations while maintaining high attitude tracking accuracy, outperforming both the unshaped control and conventional torque-shaped schemes. The approach is generalizable to flexible system with arbitrary fully actuated configurations.

With a large number of satellites and highly dynamic motion, route planning for mega-constellations faces significant challenges, such as frequent link switching and high complexity of routing calculations. To ensure efficient information transmission onboard, mega-constellations are grouped into multiple management domains with stable configurations, with the consideration of communication range and the stability of satellites' relative motion. A spatiotemporal grid (STG) is proposed to facilitate interdomain route planning, in which the Earth's surface is divided into finite grids, and then the complex dynamic intersatellite routing problem is converted into static reference trajectory optimization in the spatial domain and grid-satellite matching in the temporal domain. Considering the network perception limitation of satellites, the dynamic programming (DP) algorithm and its optimization are proposed for the routing decision phase. In the DP algorithm, the current domain searches the next routing target according to the reference trajectory. To further reduce the routing hops, the lookahead dynamic programming (LDP) algorithm is proposed to optimize routing decisions through the matching of multistep grids. Simulation results demonstrate that the proposed strategies can effectively approach minimum-hop interdomain routing without requiring global constellation information or time-consuming orbital propagation, which is beneficial for the future on-orbit autonomous application of mega-constellations.

A numerical method for computing Nash equilibrium strategies (NES) of the spacecraft time-optimal orbit pursuit-evasion game (TOOPEG) with continuous thrust reachable domain (RD) analysis is proposed. Through theoretical derivation and Monte Carlo validation, the equivalence among the minimum time of the TOOPEG problem with NES, the minimum time of a virtual single spacecraft for a time-optimal approach to the origin, and the minimum time required for the envelope of the pursuer’s RD to enclose that of the evader is established. First, the necessary conditions for NES are derived using Pontryagin’s maximum principle (PMP), converting the original bilateral optimal control problem into a 7-dimensional two-point boundary value problem (TPBVP). Then, the TOOPEG is transformed into a virtual single-spacecraft time-optimal approach problem, with the above necessary conditions. By exploiting the evolutionary characteristics of the continuous-thrust RD, the problem is further reduced to a 3-dimensional nonlinear differential equation. An improved Broyden quasi-Newton iterative (IBQNI) algorithm is employed to obtain high-precision numerical solutions, and an iterative initial value construction method based on a linearized orbit dynamic model is proposed. Furthermore, a set of criteria is developed to assess the relative spatial configuration between the RD of different spacecraft. Numerical simulations demonstrate that the proposed method achieves excellent convergence and remarkable computational efficiency.

The dynamics analysis of a multiple turntable spacecraft system equipped with three distributed payload modules focuses on addressing critical challenges in coupled motion control for decentralized and time-sensitive observation missions. Strong nonlinear coupling between the spacecraft base and turntables induces propagating disturbances and attitude instability, while real-time multi-target tracking demands precise synchronization under stringent platform stability constraints. To resolve these issues, this article proposes a fixed-time convergent non-singular terminal sliding mode controller developed through a unified relative error dynamics framework to achieve precise mission observation objectives. Incorporating fixed-time stability theory, the design integrates a piecewise switching function that simultaneously enhances both transient response acceleration and steady-state tracking precision. Numerical simulations have demonstrated the ability of the proposed controller to guarantee synchronized multi-task-tracking. Copyright (c) 2025 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)

This study tackles the critical challenge of achieving high-precision and rapid attitude maneuvers for underactuated flexible spacecraft, where rigid-flexible coupling poses significant control difficulties. A novel dual-vibration suppression attitude control strategy is proposed, seamlessly integrating scheduled input shaping, attitude path planning, and state feedback control within the Fully Actuated System (FAS) framework. This approach effectively mitigates vibrations induced by the rigid-flexible coupling while ensuring agile and precise attitude maneuvers. To address the absence of direct modal variable measurements for flexible appendages and the presence of external disturbances, a desired linear system is formulated using the FAS approach, with nonlinearity compensation provided by a nonlinear extended disturbance observer. Specifically, a two-mode input shaper, operating independently of the feedback loop, is designed to shape reference attitudes generated via sinusoidal angular acceleration path planning, eliminating residual vibrations. The proposed method demonstrates robust performance, enabling rapid attitude transitions while suppressing elastic vibrations efficiently. Numerical simulations validate the effectiveness and robustness of the control strategy, highlighting its potential for practical applications in flexible spacecraft attitude control.

As the constellation scale expands, the traditional constellation management mode imposes a substantial burden on ground stations. In order to construct a high-efficiency management mode for the low earth orbit (LEO) mega-constellation and to respond to the mission rapidly, a management strategy using distributed management domains as well as their dynamic evolution and maintenance methodology is proposed. In this paper, the distributed management domain is described as a variable topology consisting of groups of categorized satellites. The mega-constellation management topology is divided into a limited number of sub-topologies, determined by minimizing the average transmission latency and the frequency of management updates. Considering the dynamic of constellation, a method for predicting satellite management switching time is proposed, and a fast management maintenance strategy is designed to reassign satellites into new sub-topologies, ensuring a low overall update frequency of the management domain structure. Simulation validates that the management strategy divides the mega-constellation into dozens of management sub-topologies with similar structure and low-frequency management updates. Throughout the management period, each satellite remains under management with low transmission latency, and the overall management topology maintains long-term stability.

Targeting advanced engineering applications of the Earth observation, this study resolves critical challenges in dynamics modeling of large-aperture flexible appendages and precision formation control. A thin-film diffraction imaging system is designed to reduce weight, enhance resolution, and improve revisit capability. A rigid-flexible spacecraft dynamics model is derived using dual quaternion, and a fractional-order operator is employed to design an attitude-orbit integrated sliding mode controller. Asymptotic stability is mathematically proven, with a fast terminal sliding mode controller (FTSMC) introduced for comparative analysis of the fractional operator's impact on control performance. Theoretical analysis confirms the system's asymptotic stability, while numerical simulations validate the dynamics model and controller effectiveness. The utilization of dual quaternions provides an effective framework for characterizing the cross-coupling phenomena of attitude, orbit, and vibration in rigid-flexible coupled spacecraft. Fractional-order operators introduce additional tunable parameters into traditional control frameworks, thereby enhancing control flexibility and robustness.

Flexible spacecraft, characterized by infinite degrees of freedom, pose challenges in attitude control due to complex coupling effects and significant nonlinearities. This paper addresses the attitude control problem for underactuated flexible spacecraft, considering external disturbances, inertia uncertainties, and control input saturation. A novel active disturbance rejection saturated control strategy, which is based on fully actuated system (FAS) theory, is developed to achieve robust attitude stabilization. The approach involves the construction of a fully actuated attitude model for the flexible spacecraft and implementing an extended disturbance observer to estimate uncertain nonlinearities, such as elastic vibrations, system uncertainties, and external disturbances. These estimates are fed into a nonlinear feedforward compensation control. The feedback controller, designed with the direct parametric method, ensures the desired orientation with high precision. Additionally, the inclusion of a dynamic gain filter effectively controls input saturation and significantly enhances flexible vibration suppression. The simulation results validate the effectiveness of the proposed strategy, demonstrating its potential for use in underactuated flexible spacecraft attitude control in practical scenarios.

This paper studies the issue of learning radial basis function neural network (RBFNN)-based robust reconfigurable fault-tolerant configuration control for spacecraft formation flying (SFF) systems subject to thruster faults and space perturbations. To robustly reconstruct thruster faults, a novel learning RBFNN estimator is innovatively explored, in which the P-type iterative learning algorithm is utilized to online update the weight matrix of the RBFNN model and the H infinity control technique is adopted to attenuate the effect of space perturbations. Further, a learning RBFNN output-feedback fault-tolerant control (FTC) method is developed for spacecraft formation configuration maintenance with high accuracy, and the learning RBFNN algorithm is used to update and compensate the synthesized perturbation. Finally, a numerical example is simulated to verify the presented learning RBFNN-based spacecraft formation FTC approach is feasible and superior.

To investigate the real-time mean orbital elements (MOEs) estimation problem under the influence of state jumping caused by non-fatal spacecraft collision or protective orbit transfer, a modified augmented square-root unscented Kalman filter (MASUKF) is proposed. The MASUKF is composed of sigma points calculation, time update, modified state jumping detection, and measurement update. Compared with the filters used in the existing literature on MOEs estimation, it has three main characteristics. Firstly, the state vector is augmented from six to nine by the added thrust acceleration terms, which makes the filter additionally give the state-jumping-thrust-acceleration estimation. Secondly, the normalized innovation is used for state jumping detection to set detection threshold concisely and make the filter detect various state jumping with low latency. Thirdly, when sate jumping is detected, the covariance matrix inflation will be done, and then an extra time update process will be conducted at this time instance before measurement update. In this way, the relatively large estimation error at the detection moment can significantly decrease. Finally, typical simulations are performed to illustrated the effectiveness of the method.

This study investigates the issue of multi-objective mission planning for multi-payload satellite constellations via the nondominated sorting carnivorous plant algorithm (NSCPA). Observation time windows are generated, and a constraint satisfaction model is established based on multiple regional targets, satellite orbits, and characteristics of the synthetic aperture radar (SAR) payload and optical payload. A task conflict detection and resolution method is proposed to handle the task assignment among multiple satellites. Based on the existing single objective-based CPAs, a modified multi-objective NSCPA is first developed for multi-objective planning optimization using the non-dominated sorting algorithm. The effectiveness and superiority of the NSCPA are verified by a series of simulation experiments and comparisons with the traditional non-dominated sorting genetic algorithms-II (NSGA-II) and particle swarm optimization (PSO).

This paper addresses the problem of attitude control of flexible spacecraft. Considering the nonlinear system under external disturbance and model uncertainty, an attitude controller based on Fully Actuated System (FAS) theory and Sinusoidal angular acceleration attitude path can be designed to achieve the attitude maneuver with minimal residual vibration. Compared to traditional controllers, FAS is often more immune to the nonlinear factors and its control law is easier to design. FAS compound with Extended disturbance observer is designed to achieve the desired linear system when compensating for the lumped disturbance and adverse nonlinearity. Moreover, the planned smooth path can suppress the flexible vibration to great extent. Simulations show that the proposed method is tolerant to the external disturbance. And it can make the modal response superior with fast convergence and small oscillation which means our algorithm can achieve quality dynamic character in a short time. This explores the application of flexible spacecraft control of FAS.

Summary This article investigates the issue of orbit coordination control for a class of multi‐spacecraft formation systems in presence of limited communication and external disturbance. To solve the limitation of communication sources, a dynamic event trigger (DET) mechanism is developed to reduce the communication frequency between the follower spacecrafts. Subsequently, we explore a robust DET mechanism‐based distributed self‐learning sliding mode control design, in which a variable learning intensity‐based iterative learning algorithm is designed to approximate and compensate space perturbation. This approach can guarantee an event triggering sequence without Zeno phenomenon and accurate coordination control for formation configuration simultaneously. Compared with the traditional event‐triggered control and other state‐of‐the‐art approaches, the distributed DET control scheme achieves higher control accuracy of formation configuration meanwhile requires less communication resource. Finally, a series of numerical simulations demonstrate the feasibility and superiority of the event triggered control method.

A large number of sensors carried by spacecraft are facing the risk of irradiation, which may lead to the failure of sensors and affect the mission of the spacecraft. Therefore, it is significant to make the sensor work safely by attitude maneuvers. This article proposes a guidance algorithm for the attitude reorientation of rigid spacecraft, which aims to reduce the conservativeness of the traditional potential function and to solve the problem of the goal being non reachable with obstacles nearby (GNRON). While the rationality of the form design of the potential function is analyzed from the view of numerical calculation, a modified inverse-proportional potential function is designed based on it. Additionally, the anti-unwinding attitude error function is established to avoid the unwinding phenomenon of quaternions. In this paper, a set of weight assignment schemes for the potential function is proposed to obtain the maneuver path close to the edge of the attitude-forbidden zone, which reduces the conservativeness and energy consumption compared with the traditional method. Finally, the scheme can also solve the GNRON phenomenon. In the fourth section, the form design of the potential function is studied by numerical simulation, and the performance of the proposed algorithm is shown by comparative experiments.

Aiming at the complex internal structure of the satellite to be repaired in the on-orbit maintenance mission and the high requirements of the maintenance mission on the precision of robotic arm path planning, a multi-robotic arm path planning algorithm Deep Deterministic Policy Gradient RRT (DDPG-RRT) combined with deep reinforcement learning is proposed. Firstly, the initial environment is established. Then, on the basis of the traditional RRT algorithm, the idea of DDPG algorithm is introduced to set the dynamic step size to search the collision-free path between the start position and the target position of each robotic arm departing at the same time. Finally, a path optimization algorithm is introduced to smooth the planning path. The results show that compared with the traditional RRT and RRT-Connect obstacle avoidance algorithms, the average planning time, the total average path length, and the success rate of this method are reduced, which is feasible.

With the increasing complexity of industrial production and manufacturing tasks, industrial robots are expected to learn intricate operations from simple actions easily and quickly with adaption to dynamic environment. In this paper, a task-parameterized multi-task learning framework is proposed to facilitate rapid learning of operational skills for industrial robots. In this framework, a conditional Probabilistic Movement Primitives (ProMP) is firstly employed to the single-task learning. Using the conditional probability calculation, the extrapolation issue in Learning from Demonstration (LfD) is addressed, enabling robots to learn beyond teaching. Subsequently, the single-task is extended to multi-task scenario by proposing a multi-task learning approach where each single task executes an extrapolation learning. The learned skill can meet the multiple task requirements through an iterative modulation manner. The effectiveness of the proposed framework is validated through both the simulation and a 7-DoF Franka-Emika robot experiment in a predefined task scenario. Furthermore, the outperformance of the proposed method is demonstrated by comparing with the state-of-art movement primitives based learning method.

PurposeThis paper aims to investigate the attitude synchronization issue of multi-spacecraft formation flying systems under the limited communication resources.Design/methodology/approachThe authors propose a distributed learning Chebyshev neural network controller (LCNNC) combining a dynamic event-triggered (DET) mechanism and a learning CNN model to achieve accurate multi-spacecraft attitude synchronization under communication constraints.FindingsThe proposed method can significantly reduce the internal communication frequency and improve the attitude synchronization accuracy.Practical implicationsThis method requires the low communication resources, has a high control accuracy and is thus suitable for engineering applications.Originality/valueA novel DET mechanism-based LCNNC is proposed to achieve the accurate multi-spacecraft attitude synchronization under communication constraints.