This paper addresses the position and attitude control of combined spacecraft in on-orbit servicing missions, taking into account model parameter uncertainties, unknown external disturbances, and fuel-optimal constraints. A novel flexible prescribed-performance optimal backstepping controller without initial constraints is proposed by incorporating an Actor-Critic-Identify neural network architecture. First, a dynamic model of the combined spacecraft is established, with all uncertainties treated as lumped disturbances. To improve transient performance and remove initial value constraints, a flexible prescribed performance function is designed, which accommodates input saturation and decouples settling time from both initial states and controller parameters. Subsequently, a steady-state performance optimized Identify weight adaptation law is employed for rapid and accurate estimation of the nonlinear lumped disturbances. For fuel optimization, a simplified Actor-Critic adaptation law is developed, eliminating the need for complex step-by-step derivations while ensuring weight convergence. The uniform ultimate boundedness of the closed-loop system is proven using Lyapunov theory. Numerical simulations and semi-physical experiments verify the proposed method’s advantages in both steady-state and transient performance, as well as its applicability to on-orbit implementation.

Large flexible appendages can introduce persistent low-frequency vibrations that significantly degrade the attitude pointing accuracy of modern spacecraft. To address this issue, this paper proposes a hierarchical cooperative control framework for large flexible spacecraft that combines contraction-based tube model predictive attitude control with reinforcement learning-based active vibration suppression. First, a nominal model predictive controller is designed to generate reference attitude trajectories under input constraints. Then, an ancillary controller is developed based on contraction theory to drive the disturbed state toward the nominal trajectory. To improve real-time implementability, a Multidimensional Taylor Network (MTN) is employed to approximate the minimal geodesic required by the contraction-based control law, thereby reducing the online computational burden. In parallel, an Actor--Critic-based active vibration controller is introduced to attenuate flexible modal responses and reduce the adverse coupling effects of appendage vibrations on attitude motion. Lyapunov analysis establishes the robust convergence property of the attitude-control subsystem under bounded disturbances, while the cooperative effect of the vibration controller is validated through comparative simulations. Numerical results show that the proposed framework achieves faster attitude convergence and more effective vibration attenuation than the baseline methods under nominal and perturbed conditions.

The complex surface configuration, tumbling motion, and surrounding debris environment of failed spacecraft pose significant risks and challenges to on-orbit capture and servicing missions. To ensure both safety and mission success under such conditions, this paper proposes a dual-layer model predictive control (MPC) strategy. In the upper layer, a Control Lyapunov Function (CLF) is employed to guarantee convergence, while a relaxation variable is introduced to prevent overly strict constraints, ensuring fast and flexible convergence of relative position and attitude. In the lower layer, Control Barrier Functions (CBFs) are used to impose strict safety constraints on multiple dynamic obstacles. A deadlock detection and adaptive reference adjustment mechanism is introduced between the two layers to effectively avoid local optima. Simulations under multiple initial conditions demonstrate that the proposed method achieves millimeter-level position accuracy and 0.03 degrees attitude synchronization, while effectively avoiding collisions with the target body, solar panels, and debris under external disturbances. The approach maintains near-global optimality while emphasizing safety, providing a feasible and robust solution for micro-nano satellite on-orbit servicing missions.

Star sensor is disturbed by strong straylight, which increases the gray level of the captured star map, and this leads to invalid detection of star points and affects the high-precision location of the centroid. To address this issue, we propose a star centroid localization method based on gradient-oriented multi-directional local contrast enhancement. First, the background gray level distribution patterns of star sensors under various actual straylight interference conditions are analyzed. Based on this analysis, a background imaging model for complex operational scenarios is established. Finally, simulations are conducted under complex conditions with straylight images to test the star point detection rate, false detection rate, centroid localization accuracy, and statistical significance testing. The results show that the proposed algorithm outperforms the TOP-HAT, MAX-BACKG (Max-Background Filtering), LCM (Local Contrast Measure), MPCM (Multiscale Patch-Based Contrast Measure), and CMLCM (Curvature-Based Multidirectional Local Contrast Method for Star Detection of Star Sensor) algorithms in terms of star point detection rate. Additionally, the RMSE centroid localization error is achieved with 0.1 pixels, demonstrating its ability to effectively locate star centroids under complex conditions and meet certain engineering application requirements.

To address the limitations of current micro-nano satellites in on-orbit monitoring of non-cooperative targetssuch as inadequate adaptability in attitude control dynamics, lack of coupled orbit attitude control strategies, and insufficient handling of state constraintsthis paper establishes a six-degree-of-freedom relative motion dynamics model for spacecraft approaching non-cooperative targets. The model systematically incorporates practical engineering constraints, including input saturation and velocity limits. By integrating Control Barrier Functions (CBF) to formulate obstacle avoidance strategies, a robust integrated orbitattitude control method based on Model Predictive Control and Control Barrier Functions (MPC-CBF) is proposed. The proposed method provides both theoretical support and a technical framework for on-orbit servicing missions involving micro-nano satellites, demonstrating strong potential for practical applications.

In order to combine micro-nano satellites into ultra-large variable structure spacecraft, the design of relative attitude repeatedly adjustable docking mechanism with high precision is the key problem. Based on Stewart mechanism, a kind of high-precision relative attitude repeatedly adjustable docking mechanism was designed. Aiming at the problem of relative attitude high-precision adjustment after docking locking, the transfer mechanism of attitude adjustment error of docking mechanism was analyzed, and the transfer model of attitude adjustment error was established. The theoretical attitude adjustment accuracy was obtained through simulation calculation. By forming a closed-loop control system with the laser sensor and Stewart mechanism, the error compensation algorithm of the pose control system was designed, the high-precision adjustment of the relative pose was realized. The dynamic model was established in the scenario of two-module relative attitude adjustment, and the driving force variation law of each telescopic rod motor was analyzed according to the motion trajectory of attitude adjustment. Simulation analysis and real object attitude adjustment test show that the weight of the docking mechanism is only 2.43kg,the radius of the envelope is only 10cm,the accuracy of the three-axis attitude adjustment can reach +/- 0.02 degrees,and the maximum attitude adjustment load of the docking mechanism is 65N,which can be applied to the precise allostery of micro-nano assembly spacecraft.

In large-scale satellite constellations, the efficiency of inter-satellite communication is paramount. Traditional topology control strategies, such as the Manhattan configuration, provide stable links but can result in indirect communication paths, affecting the efficiency of information transfer. This paper addresses this issue by proposing an innovative “3 + 1” dynamic topology control scheme. The scheme retains three static links determined by the relative angular velocity and acceleration while introducing a dynamic link based on distance and angular velocity constraints to optimize the link duration and overall network communication efficiency. To address the complexity of matching dynamic links, this paper introduces an elite strategy-based maximum weighted matching algorithm for general graphs. Compared to traditional greedy algorithms, our proposed algorithm significantly improves the link duration and topological stability. Through simulation experiments comparing communication delays between Xiamen and Los Angeles, our results show that the proposed dynamic link scheme substantially reduces the average delay, enhancing the efficiency and flexibility of inter-satellite communication. This research not only extends the duration of inter-satellite links but also provides new perspectives and methodologies for further studies on inter-satellite topology control strategies.

Aiming at the problem of precision decline caused by orbital perturbations during the descending orbit interception of thin film spacecraft,an orbital control optimization algorithm based on optimal attack and sideslip angles is proposed.Firstly,the algorithm calculates the interceptable region based on the orbital dynamics characteristics of the thin film spacecraft,then determines whether the target is within the region to narrow down the search range for the optimal orbit.Drawing inspiration from the strategy used in reentry spacecraft which controls attack and sideslip angles,the algorithm seeks to minimize the miss distance as the objective function while subject to the constraint of fixed attack angle for thin film spacecraft.The particle swarm algorithm is employed to find the optimal solution for the attack angle.Lastly,to mitigate the effects of non-spherical Earth perturbations,a slight adjustment to the normal direction of interception orbit is achieved by introducing sideslip angles,thus enhancing the interception probability.Simulation demonstrate the thin film spacecraft can intercept the co-planar targets in low earth orbit with good terminal accuracy under both ideal gravitational filed and non-spheriacl perturbation gravitational filed.The work can provide a new idea for the removal and mitigation of space junk,and also has a certain reference significance for the development of new low-cost orbital interception.

Aiming at the high-precision pointing requirements of on-orbit splicing or formation, a high-precision pointing control based on visual pixel deviation is proposed. First, the telephoto camera is used to identify the cooperative target at the sub-pixel level, and the pixel deviation of the target center in the center of the camera field of view is used as the pointing control amount, and the relationship model between the target pixel and pointing angle is established; on this basis, the momentum wheel is used as Output torque, the control model of pixel offset and output torque is established, and relatively high-precision pointing control is realized. The pointing control experiment of the single-axis air bearing turntable shows that the pointing angle resolution of a single pixel of the camera reaches 0.0037°, the pointing control accuracy reaches 0.0091°, and the pointing control stability reaches 0.01°/s, which verifies the high accuracy and effectiveness of the control scheme sex.

The prevention of rock burst is a major problem in coal mining.In recent years, with the gradual shift from shallow layer to deep layer of coal mining, the number of rock burst in coal mines has increased.Rock burst is a serious threat to the safety of coal mine workers and will bring huge economic losses, so it is particularly important to study the prediction of rock burst.The traditional prediction method can only analyze a small amount of precursor information before the occurrence of rock burst, and can not predict the change trend of future rock burst related signals according to the historical information.In order to explore the prediction method of rock burst, the research group selected rocks from coal mine with rock burst, and used TYJ-500KN microcomputer controlled electro-hydraulic servo rock shear rheological test system and SH-II acoustic emission system to carry out rock burst similarity simulation experiment.The compressive strength signals and acoustic emission signals collected in the experiment are fused, and the data are predicted by Long Short-Term Memory neural network（LSTM） with memory properties.The results show that the curve fitting between the predicted data and the actual analysis data is high, and the maximum root mean square error of the data is less than 0.6.The LSTM model has an excellent research prospect for the prediction of rock burst.

针对模块航天器在轨拼接曲面优化、曲率极值问题,提出了一种基于模块间隙约束的"球冠-平面"辅助映射法,该方法不仅可以规划模块航天器如何构成目标曲面,还可以获得该曲面的极值.该方法以正六棱柱模块航天器为单位模块,将模块按由"球冠-平面"映射的圈层排列张成目标球面,构建了拼接曲面的数学模型.鉴于工程上对机构调整有限导致的相邻模块间隙限制问题,在算法中引入了碰撞检测(DC)约束参数;通过遗传算法寻优,获得目标曲面布局的最优解.最后仿真表明:该算法可以有效获得曲面布局的最优解.

To perform indicator selection and verification for the on-orbit fault reconstruction of a giant satellite swarm, a hybrid multi-objective fault reconstruction algorithm is proposed and then verified by Monte Carlo analysis. First, according to the on-orbit failure analysis of the satellite swarm, several optimization indicators, such as the health state of the satellite swarm, the total energy consumption of reconstruction, and the balance of fuel consumption, are proposed. Then, a hybrid multi-objective fitness function is constructed, and a hybrid multi-objective genetic algorithm is used to optimize the objective function to obtain the optimal reconstruction strategy. Finally, the algorithm is statistically verified by Monte Carlo analysis. The simulation results not only show the algorithm's validity but also reveal the relationship between the number of satellite faults and the health of the satellite swarm. From this, the maximum number of faulty satellites allowed in the giant satellite swarm is calculated, which is significant for assessing the swarm's health.

当前在综采工作面中液压支架群自动跟机快速移架过程普遍存在较大的同步误差.针对此问题,本文以液压阀的流量为控制量,以液压杆位移为输出量,建立三台液压支架移架过程的同步控制系统,将四种经典的耦合同步控制策略与模糊自适应积分分离PID控制相结合,利用AMESim-Simulink联合仿真软件进行仿真实验,通过稳定性实验与抗干扰实验分析比较四种控制策略的实验结果,得到最优的控制策略,以减小移架过程中的同步误差.结果表明:在稳定性实验中,均值耦合同步控制策略同步误差小于 0.7 mm,比主从同步控制、并行同步控制、交叉耦合同步控制精度高;在抗干扰实验中,均值耦合同步控制策略同步误差小于0.8 mm,比主从同步控制、并行同步控制、交叉耦合同步控制受影响小.以上研究结果表明,均值耦合模糊自适应积分分离PID控制方法控制精度高、抗干扰能力强、系统同步误差最小.

Aimed at solving the problems of large fuel consumption, imbalance and long time-consumption in the application of traditional cluster aggregation algorithm in spacecraft cluster planning, an energy optimal clustered collision avoidance algorithm based on centripetal aggregation was proposed. Firstly, based on the relative motion equation of the cluster and the finite-time energy optimization model, the energy optimal model of adaptive centripetal aggregation was established by the algorithm. On this basis, for the problem of long time-consumption and collision, a cluster collision avoidance algorithm based on energy optimization was proposed. The safe distance vector between modules was used as the collision avoidance constraint, and the energy consumption was used as the clustering algorithm index. The simulation results show that the algorithm can adaptively select the center of cluster clustering, effectively avoid collision, reduce the total energy consumption of cluster aggregation and the imbalance of energy consumption between modules,so that the working fluid consumption is globally optimal, and the time consumption is only one ten thousandth of that of the conventional genetic algorithm. This algorithm provides an idea for rapid and safe clustering of clusters.

Piezoelectric micromechanical ultrasonic transducers (pMUTs) are new types of distance sensors with great potential for applications in automotive, unmanned aerial vehicle, robotics, and smart homes. However, previously reported pMUTs are limited by a short sensing distance due to lower output sound pressure. In this work, a pMUT with a special dual-ring structure based on scandium-doped aluminum nitride (ScAlN) is proposed. The combination of a dual-ring structure with pinned boundary conditions and a high piezoelectric performance ScAlN film allows the pMUT to achieve a large dynamic displacement of 2.87 μm/V and a high electromechanical coupling coefficient (kt2) of 8.92%. The results of ranging experiments show that a single pMUT achieves a distance sensing of 6 m at a resonant frequency of 91 kHz, the farthest distance sensing registered to date. This pMUT provides surprisingly fertile ground for various distance sensing applications.

现有煤矸石分选方法主要依据人工设计特征对煤矸石进行识别,但特征提取过程复杂,准确率也较低.随着人工智能技术的快速发展,智能选矸成为解决煤矸石分拣问题的重要研究方向.为提高煤与煤矸石分类准确率,本文提出了一种基于AlexNet网络和风格迁移技术改进的煤矸石分拣方法.选用3×3的卷积核代替原AlexNet网络前几层中较大的卷积核,利用BN层代替LRN层和Dropout,并采用风格迁移数据增强法提高煤与煤矸石数据集的多样性.研究结果表明,与原始的AlexNet网络相比,该方法的准确率提高了1.8％,损失率下降了2.0％.此方法不仅能够满足煤与煤矸石实时检测的要求,而且具有更高的识别精度,能有效应用于煤矸石识别.

Real-time health assessments are of great importance for the safe and stable operation of in-orbit swarms. To solve the problems of existing real-time health assessments of microsatellite swarms, such as the difficulty of selecting a multisource and assessment calculation normalization, this paper proposes a real-time health assessment method applicable to mission-oriented swarms. The method divides the microsatellite swarm into three levels: single satellite, intersatellite communication link and swarm effectiveness, which establish a multilevel index system by adopting the reliability evaluation based on random failure and failure by loss, a health evaluation based on natural connectivity, and a real-time dynamic analysis based on swarm topology. For the swarm effectiveness during the mission, the multilevel index and the entropy weight method are used to construct the effectiveness evaluation model of the whole swarm, and the health state evaluation of the swarm is realized based on the variable weight principle. The simulation results show that this method can quantify the health state of the microsatellite swarm in real-time, and it can predict the health state after the fault without maintenance.

在有风浪的复杂海况下,需要自主着舰的无人机与舰船两者相对运动带有极大不确定性,为了提高无人机着舰时相对定位以及控制的精度,确保无人机着舰时的安全性与可靠性,提出一种通过差分对流层误差的相对精密单点定位技术(relative precise point position,RPPP).该技术仅依靠数据链和载波型卫星定位接收机,消除相同环境下卫星定位相同误差,获得精确相对定位.将比例导引与LQR(linear quadratic regulator)控制器相结合,解决了无人机着舰入射角偏差较大的问题,提高了无人机着舰末段高程方向及入射角度的控制精度.对无人机着舰轨迹进行规划,建立无人机着舰的运动模型,设计无人机着舰横向和纵向的控制律,搭建无人机自主着舰的仿真平台.仿真结果表明,采用上述算法着舰误差控制在0.2 m以下,入射角偏差在10-3量级,可满足无人机着舰要求.

为准确预测冲击地压发生的可能性,采用模糊C均值聚类算法分析三轴声发射实验采集的压力和声发射特征信号,确定冲击地压各指标的危险等级及其对应的模糊集合,建立标准模型库,随机选取一组新数据,使用欧氏贴近度的方法将其与模型库相匹配,预测对应冲击地压的危险等级.结果表明,使用欧氏贴近度的方法确定了冲击地压危险情况,最大贴近度值为0.944,冲击地压危险等级为强危险.

To solve the problem of balance control in dynamic movement of two-wheeled self-balancing pendulum robot, a dynamic balance control method based on adaptive machine learning is proposed based on theoretical analysis of the cause of balance. Firstly, a kinematics model of two-wheeled self-balancing pendulum robot is established. Through numerical calculation and analysis, the root cause for dynamic balance of two-wheeled self-balancing pendulum robot is obtained. On this base, adaptive machine learnings are proposed to control the dynamic balance of two-wheeled self-balancing pendulum robot. The possible lateral movement of robot caused by dynamic balance control is analyzed. Finally, balance simulation test is conducted, which shows that the robot can easily lose balance and overturn without adaptive machine learning. The comparison of simulation test has verified that the proposed dynamic balance control method can effectively control the dynamic balance of two-wheeled self-balancing pendulum robot.