An adaptive sliding mode control method is proposed for the control problem of a quadrotor UAV composed of six degrees of freedom under model uncertainties and unknown disturbances. This method can be used to realize position and attitude tracking control of quadrotor UAV. Firstly, based on the dynamics quadrotor system, the fully actuated and under-actuated subsystems are divided. The model uncertainties and unknown disturbances without upper and lower limit constraints are fully considered, and the lumped disturbance terms of each subsystem are extracted; Then, with the help of radial basis function neural network, the real-time approximation and estimation of the equivalent controller containing the extracted lumped disturbance terms are inplemented in progress. At the same time, adaptive control method is used to estimate the approximation error term. The sliding mode controller with the estimated values of the equivalent controller and approximation error terms and the corresponding adaptive update laws are designed. Based on Lyapunov theory, the reachability and convergence of the sliding mode surface where the state trajectories of each subsystem lies are analyzed and introduced. Finally, the comparative simulations are used to verify the effectiveness of the proposed method fairly well.

Aiming at unexpected the sudden change in inertia parameters of spacecraft on-orbit servicing, real-time identification methods of inertial parameters based on on-orbit attitude and control information are proposed, and recursive least squares (RLS) and extended Kalman filter (EKF) identification algorithms are designed. Adaptive forgetting factors are introduced into the RLS algorithm, which assign weights of prior data and current data during each iteration process to ensure the identification value tracking in time. In the EKF algorithm, the influence of parameter variation on the prior prediction covariance is defined, and it is substituted to update the prediction covariance matrix to solve the mutation of inertia parameters. Under consideration of the mutation in inertia parameters, the simulation results show that the identification accuracy of RLS and EKF can reach 1.5% and 1%, and the identification time is better than 30 s and 40 s respectively; In the scenario of time-varying inertia, both methods can achieve on-orbit identification of inertia parameters, and the identification accuracy fulfills the requirements of the attitude control system.

The design scheme and in-orbit verification results of the high-precision star tracker is presented, which is used in the Shenzhou series of spacecraft in China. In the lens design, a front-placed diaphragm structure is adopted to meet the needs of miniaturization and long-term applications; In the overall structure design, a "frame combination wrap-around" integrated structure is adopted to focus on lightweight and stability; In the circuit design,radiation-resistant reinforced APS image sensors, processors and ASIC are applied to ensurance of high-sensitivity detection and high-reliable information processing throughout the service life; In the algorithm, clustering extraction, fast triangular recognition, curtain compensation and dynamic adjustment of exposure time, etc. are used to achieve key performance indicators such as precision, update rate, dynamic and capture; In addition, the thermal stability of the whole machine is improved to ensure that the performance of the star tracker can be maintained. The star tracker is successfully applied to a series of major space projects, including manned spaceflight, lunar exploration and Beidou-3 which have more than 200 units in orbit operation.

Aimed at the problem that traditional target tracking methods require prior position information of the target which are not suitable for non-cooperative target tracking, a target tracking method based on wide-angle camera image error for video satellite is proposed. A wide-angle camera imaging model is firstly established, and then the difference is calculated between the projected position of the target in the camera image plane and the expected position. The relative error, angular velocity and attitude error between the target and the small video satellite are calculated by image error, which are used as feedback terms to design a nonlinear controller. Finally, the stability of the system is demonstrated by using the Barbalat’s lemma. The simulation results show that the target driven to the desired position in the image plane can be effectively controlled in a wide field of view of a wide-angle camera and the effectiveness of this method is verified by Tiantuo-2 satellite on orbit data.

Regarding meeting the task requirement of rapid missile launch, a fast firing data solving method based on neural network is proposed. Firstly, the mapping relationship among terminal velocity, altitude, velocity inclination and firing data is established, and the LM optimization neural network model is derived. Then, based on Bayesian regularization theory, the BP neural network structure is designed, and the optimized network structure which can meet the accuracy requirements is obtained. Finally, Newton iteration method is used to generate the database as training set which is used to train the neural network, so that the network model with optimized parameters is obtained, and the simulation is implemented. The theoretical and simulation results show that the rapid calculation of the firing data before shooting can be achieved by applying this method.

The requirements of the flexibility of aerospace control system are extensively analyzed in this paper，and the challenges are deeply discussed，which are concentrated on the system level and the device level. The design concept of the flexibility of the system level and the device level is proposed in innovation，and the key technical path of the flexibility of the system level and the device level is further elaborated，such as rapid assembly and interoperability management of system software and hardware，multi-level communication interconnection，flexible integrated conformal layout and analysis，and verification of the adaptability of flexible electronics to the aerospace environment，and the development trend of the flexibility of the aerospace control system is finally visioned in terms of integrating innovative technologies，strengthening cross domain cooperation，establishing standards and specifications，and expanding and deepening applications.

In order to solve the problem that the filtering result of RIMU/GNSS integrated navigation system based on filtering method is unstable under the condition of large maneuvering of carrier, an estimation method based on factor graph is proposed. The state equation and measurement equation oriented to the redundant inertial navigation system are established, and the redundant inertial data are fused into the carrier coordinate system three axes. A data fusion method based on factor graph is established, and the fused inertial data and satellite information are abstracted as factor nodes, and the state information is abstracted as variable nodes. The cost function including inertia factor and GNSS factor is established and the state quantity is estimated in a nonlinear optimization way. The reslult of numerical simulation shows that performance of using the factor graph method can effectively reduce the position error of the carrier and the root mean square error is obviously degraded than that of the Kalman filter.

In response to the requirements of aerospace electromechanical servo systems for fast step response, no overshoot and high steady-state accuracy during tracking continuously changing signals, a composite control is involved on the basis of position-speed-current triple closed-loop feedback control with introduction of feedforward control. The tracking accuracy of continuously changing signals without reducing the dynamic performance and stability of the system is improved by using this control strategy. The design methods of closed-loop controller and feedforward controller are analyzed.Regarding the noise sensitivity of the feedforward function designed by invariance principle, a designed method based on error coefficient method is developed, and experimental verification is conducted. The experimental results show that the servo mechanism system can respond to step commands quickly without overshoot. The system has good tracking accuracy for continuously changing signals, and the system bandwidth has been expanded. The experimental results demonstrate the effectiveness and practical feasibility of the control method proposed in this paper.

The transfer strategies for multi-objective missions around the Earth-Moon Lagrange points are studied and a two-impulse transfer strategy that allows spacecraft to move between near-rectilinear halo orbits and distant retrograde orbits is designed. Firstly，the spacecraft's orbital dynamics model is established in the synodic frame. Then，the overall design of the transfer strategy is implemented，the relevant optimization variables are analyzed，the objective function and constraints are determined，and the transfer strategy design problem is transfered into a trajectory optimization problem. Furthermore，the feasibility of genetic algorithms and particle swarm optimization algorithms for this specific problem is verified for solving the transfer trajectory. A numerical method is presented through this research by applying genetic and particle swarm optimization algorithms to transfer strategies design of halo orbits，which focuses on recent interest in near-rectilinear halo orbits and distant retrograde orbits. The proposed optimization method has ability of effectively resolving the orbital transfer design problem without prior information and can be applied to various transfer scenarios.

A guidance law with variable control weight is proposed，which is based on the optimal control method for intercept different types of maneuvering targets by using air-defense missile. A state equation of relative motion between missile and target in the longitudinal plane is set up，and an indicator function based on variable control weight and line of sight angular velocity constraint is designed，furthermore，the optimal guidance law related to weight coefficients is derived by using the minimum numerical principle. Simulation experiments are implemented for different types of maneuvering targets，and the results indicate that the performance of the optimal guidance approach proposed in this paper is superior to traditional proportional guidance method. The line-of-sight angular velocity convergence is fairly quick，which can form preferable reverse orbit situation. Furthermore，regarding targets under different maneuvering modes，the weight of the optimal guidance law can be adjusted to match the optimal control parameters of each maneuvering target.

Regarding the significant impact of code generation techniques based on large language models （LLMs） on software productivity and their broad application prospects to the aerospace field，the latest research progress on this kind of technology is reviewed from three aspects: problem background and definition，typical technologies and their potential application scenarios in the aerospace domain，and application evaluation methods，with the aim of providing guidance and insights for related research on code generation techniques in the aerospace domain. Firstly，the basic capabilities of LLMs are discussed on code generation according to the features of code generation problem definition and LLMs structures. Then，the main methods for code generation are elaborated，including pre-training，instruction fine-tuning，prompt engineering and retrieval-augmented generation as well as their potential application scenarios to the aerospace field. Next，due to the perspectives of semantic similarity and validation datasets，the popular methods are reviewed for evaluating the results of LLM-based code generation techniques and their characteristics and limitations are analyzed. Finally，the challenges are presented and future improvements are proposed.

Aiming at the problem of multi-coverage of hot regions,a design scheme of common ground track constellation with regression orbit attribute is applied,and a design method based on genetic algorithm(GA)for optimization of the orbital parameters of a single satellite and analytic method for solving the orbital parameters of a constellation is proposed in this paper. Firstly, a regression orbit model for muti-coverage of hot region is established.Secondly,by taking the optimal coverage effect of a hot region as the performance index,genetic algorithm(GA)is used to optimize and solve the orbit parameters of a single satellite.Finally,the orbit parameters of the constellation are solved by analytical method. The results of theoretical analysis and simulation totally show that the design method can achieve periodic multi-coverage of hot regions and higher time resolution ratio, which present fairly good engineering application value.

A design method for an active disturbance rejection controller based on complementary sliding mode is proposed to address the position and attitude control problem during the point cloud data collection process of quadrotor unmanned aerial vehicle （UAV） that carries a light detection and ranging （LiDAR） for power transmission lines. Regarding the problems of strong coupling，non-linearity，and external disturbance effects under the complex environment of quadrotor UAV，a finite time convergent extended state observer is adopted to estimate the state and lumped disturbances of the quadrotor UAV dynamic system，which introduces the observed lumped disturbances into the active disturbance rejection controller for feedforward compensation. At the same time，complementary sliding mode manifolds are established，and the exponential power function and the integral form of sign function are used to ensure the continuity of the active disturbance rejection controller. Finally，a rigorous proof of the asymptotic convergence of position and attitude tracking errors is provided，which is based on the Lyapunov analysis method，and the simulation results show that the proposed method has higher control precision and can effectively suppress different forms of external time-varying disturbances.

In order to fulfill the demands for rapid and precise attitude adjustment during the docking process of solar arrays, and to resolve the challenges associated with manual adjustment,this study proposes a leveling strategy, which can update the kinematic parameters of the AAM according to the ground leveling situation, uses the laser tracker to obtain the pose required for leveling, applies closed-loop joint position control based on kinematic inverse solution to realizing the leveling of the moving platform, avoids the false leg in the leveling process through implementation of the traditional outrigger lifting and leveling method, and realizes the automatic adjustment of the AAM from the state of the outrigger stowed away to the state of touching the ground as support and then to the state that the moving platform is automatically adjusted to the horizontal plane level. The feasibility of the leveling strategy is verified through simulation, which provides a solution to false leg-leveling in the engineering application of AAM during solar wing docking.

In this paper, a novel predefined-time line of sight (LOS) angle rate convergence guidance law is proposed for the diverse engagements in three-dimensional (3D) scenarios. By using this guidance law, the LOS angle rate can be converged to zero in an arbitrarily prespecified time, which is independent of the initial conditions and control parameters. Besides, there exists an exact upper bound of the convergence time. Firstly, a planar guidance law is designed to introduce guidance commands in two-dimensional (2D) scenarios by decoupling the 3D engagement model. Then, the guidance commands can be functional in 3D scenarios by the theoretical analysis. Finally, simulations are implemented to validate the guidance law and show the effectiveness of proposed method.

Aiming at the demand of high-precision detection for the distributed spatial optical interference, a cooperative control system design scheme is proposed in this paper to address the problem of insurmountable internal and external interferences in the cooperative pointing of distributed detector platforms. Firstly, dynamics modeling of the distributed detectors and analysis of the interference mechanism are implemented. Then, on the basis of that, a distributed interference observer and an RBF network interference learning observer are designed for analyzing and separating the perturbation variables from other state quantities of the system, which are used to reduce the influence of perturbation uncertainties on the system stability. Furthermore, an attitude tracking controller is designed to eliminate uncertain perturbations of the system. Finally, simulation results show the effectiveness of the proposed design scheme and inspire the design of cooperative control system for distributed detector platforms.

In order to improve the reliability of the liquid rocket engine, aiming at solving the liquid rocket engine fault diagnosis problem, a kind of fault diagnosis model based on the kernel principal component analysis (KPCA) and the ICOA-BP algorithm is proposed in this paper. The feature extraction and dimensionality degradation of measured parameters are implemented by using KPCA algorithm which ensures sufficient features amount extracted and coming together by reducing the complexities of the data and the computational cost. And an improved Coati optimization algorithm (ICOA) is proposed to optimize the BP neural network, aiming at improving the diagnostic accuracy of the BP neural network. The algorithm is validated by using liquid-oxygen-methane rocket engine test data, and the experimental results show that the ICOA-BP algorithm exhibits faster convergence speed and higher optimization finding accuracy compared to the COA-BP algorithm. The diagnostic accuracy of ICOA-BP algorithm can reach 96.5% on the data extracted from KPCA features, which is respectively 3.5% and 3% higher than the diagnostic accuracy of BP neural network and Support Vector Machine (SVM). Compared with particle swarm algorithm (PSO) and genetic algorithm (GA), ICOA-BP algorithm demonstrates better searching ability for the global optimal solution.

A solid strap-on launch vehicle joint swing control scheme is proposed, which is dedicated to handle large range thrust variation and the non-synchronous thrust among solid boosters. Firstly, the combustion chamber pressure is used to estimate the real-time thrust of each solid booster, and the controller parameters are accordingly modified on-line due to the thrust variation. Secondly, by adopting the feed-forward control to eliminate the loss of thrust synchronism. Finally, the real time swing subsidence angle compensation for solid booster is adopted to solve the effect of pivot point excursion. The simulation results show that the proposed adaptive control scheme is able to efficiently solve control matters caused by the thrust uncertainties and the non-synchronization thrust among solid boosters, which takes advantage of increasing the attitude control precision with large scale and improving the launch vehicle’s adaptive capability in the real flying environment.

Regarding the ascent trajectory of horizontal take-off and landing reusable launch vehicles，a simplex-pseudospectral loop optimization algorithm is proposed. By optimizing the control parameters of the horizontal run section，the initial value of the ascent section is adaptively generated，and taking a certain horizontal take-off and landing reusable launch vehicle as an example，the trajectory optimization design simulation of the launch vehicle from taking off to climbing to the handover point is completed by using the simplex-pseudospectral double-loop optimization algorithm，which verifies the feasibility and effectiveness of the proposed method. On this basis，the influences of engine thrust and sensitive parameters of the flight trajectory on air-breathing mode flight profile and remaining mass are studied. At the same time，a design method of air-breathing mode power compensation is proposed. By comparing with the conventional design method，fuel consumption is further reduced and the carrying capacity of the reusable launch vehicle is improved.

Aiming at the orbit determination of non-cooperative continuous low-thrust maneuvering spacecraft，a rapid pre-identification method of thrust acceleration based on single-arc orbit determination is proposed. Based on the relationship between satellite orbit parameters and acceleration，the single-arc orbit determination results of two radar observations with a certain time interval are used to inversely solve the tangential acceleration of the spacecraft under continuous tangential thrust，and fairly smaller solution error is remaining under the condition of sparse data in a short time by using this method Which is applied respectively to the orbital climb of Starlink，OneWeb and the Qianfan constellation. The results show that when the observation interval is greater than 11 h and 15 h separately，the proposed method can realize the rapid pre-identification of the tangential thrust acceleration of Starlink and OneWeb satellites，and the solving error is less than 2%. The calculation results can be used as initial values for precise orbit determination of continuous low-thrust maneuvering spacecraft.

According to calibration problem of ten redundant laser gyroscopes ‘three-autonomy’ strapdown inertial measurement units, A calibration model and calibration scheme are deduced, which includes five-axis gyros and five-axis accelerometers. The ten-axis redundant inertial measurement unit is divided into two groups known as straight assemble X\Y\Z and oblique assemble S\T. A system level calibration method is adopted for the straight assemble, by establishing a state equation about the calibration error model, taking navigation speed error as the measurement, and estimating the calibration error parameters through Kalman filtering. Using the calibration results of the straight assemble as reference, separate calibration models are established for the accelerometer, gyros scale coefficient and gyro bias. Finally, the calibration of ten redundant laser strapdown inertial units is verified by combining the 19-position system-level calibration method with the discrete calibration method. The calibration results are correct and the characteristics of the calibration errors are analyzed.

According to the position and attitude control problem of quadrotor unmanned aerial vehicle （UAV） with external disturbances and time-varying loads，a parameter adaptive sliding mode control method is proposed，which is based on the parameter adaptive method and sliding mode control theory.The external disturbances and time-varying loads of quadrotor UAV are estimated and compensated by using parameter adaptive method so that the quadrotor UAV can be enabled to resist the disturbances caused by changes in time-varying loads and the capability of high-precision position and attitude control can be achieved. In the end，the Lyapunov stability theory and simulation results fully verify that the proposed method can effectively degrade the adverse effects of unknown disturbances and time-varying loads on the control system.

In order to achieve rapid and accurate recognition of combat intent in complex battlefield environments with fewer air combat data samples, a combat intent recognition model based on meta-metric learning framework is proposed.Regarding received small sample data during air combat intent recognition, a two-way gated recurrent unit network based on the air combat temporal data are developed to realize effective feature extraction, and the attention mechanism is introduced for promoting the network to fully extract the temporal core features of the air combat data when facing the small sample data are merely available for obtaining the inter-class differences which finally achieve a fairly higher recognition accuracy and recognition speed.Simulation results show that the model proposed in this paper has better accuracy and real-time performance for air combat target intent recognition, especially in the case of small sample data.

In order to solve the problem of positioning and reliable recovery of some important structures of aircraft after flight test, a highly reliable positioning system based on Beidou and GPS dual-mode module is designed. The system uses the BDM 910 module integrated with GPS/RNSS (Radio navigation satellite system) module and RDSS (Radio determination satellite system) module as the core positioning device is used in the system, and the BDS (Beidou navigation satellite system) frequency point and GPS frequency point navigation messages are received through dual links and four antennas redundancy. While effective satellite navigation signals are captured, the system own position information is resoved in real time. The location information is sent to the search device in real time in the form of Beidou short message, and the landing point coordinates of the aircraft are finally determined. The problem of positioning and recovery of relevant important structures is solved in the flight test in a complex environment. The positioning system has the ability to analyze the positioning data and the communication information of the positioning device in real time, the data analysis rate is less than 5 s, the positioning accuracy is less than 10 m, the communication success rate is more than 95%, the system is continuously running and lasts more than 4 hours, and the positioning is highly reliable.

The algorithm of the integrated celestial navigation combined accelerometers with X-ray pulsar sensor is researched. Firstly，the inertial navigation algorithm is provided for spacecraft based on the heliocentric inertial reference frame，and the accelerometer drift is estimated by the phase difference of the inertial navigation and X-ray pulsar sensor in pulsar direction based on PI filter. Then，the algorithm of the integrated celestial navigation combined X-ray pulsar sensor with accelerometers based on the time of arrival （TOA） of the pulsar pulse is proved. Lastly，simulation results show that the algorithm of the integrated celestial navigation is effective.

The anti-peak circuit of the timing attitude control system of the launch vehicle adopts a "diode+resistor" circuit and a "resistor+diode+voltage regulator diode" circuit. MULTISIM is used for simulation and experimental verification. It is found that the theoretical solenoid valve shutdown time becomes shorter when anti-peak resistance grows larger，and the voltage regulator diode voltage goes larger，separately. Regarding the same electromagnetic valve shutdown time index requirements，a lower reverse voltage produced by using the method of increasing the voltage regulator than using the method of increasing the resistance； Due to the precisely controlling of the flows of fuel and gas that are ensured to be delivered to the engine in the predetermined ratio and time，the boost valve，relief valve and auxiliary power solenoid valve.play an important role of adjusting regulating pressure and protecting safety in the attitude control system，which maintain the stability of the launch vehicle's attitude and flight safety. Therefore，their shutdown time and anti-peak voltage need to be precisely controlled.

A predictive control method for electromagnetic switching valve is proposed for attitude control of spacecraft. Based on the predicted control time and nozzle layout，the ignition logic of electromagnetic valve is designed and the force of the nozzle is utilized to cancel out each other，so that the control torque action time can be adjusted arbitrarily during the control cycle. The simulation analysis shows that compared with conventional pulse width modulation techniques，the predictive control method allows the solenoid valve to achieve precise attitude control without being limited to the minimum continuous opening time.

A method aiming at the formation control problem during the reentry of multi-unpowered vehicles is discussed in this paper. Based on second-order system consistency theory of virtual leader, a distributed formation keeping and control algorithm switching of adjustable assembly time is proposed by selecting optimal coordination variables and introducing a special transition link. The altitude of multi-vehicles are allowed to be changed in a certain range by using this proposed solution that considers the flight ability under the restraint of multi-vehicles formation mission and then realizes the accurate online control of the relative transverse and longitudinal range. Simulation results show that the proposed algorithm can achieve the desired control effect in scenarios of formation assembly and keeping, formation configuration switching and formation lateral maneuver. The algorithm takes into account the effects of the earth’s curvature and rotation on the reentry dynamics, and can adapt to random aerodynamic coefficients and atmosphere density pulling by good robustness.

A dual-arm space robot finite time compliant capture strategy for non-cooperative targets is proposed. Firstly, the end-effector dynamic model of generalized coordinates presented by end-effector pose degree of freedom based on the free-floating space manipulator is established. On the basis of this, a global fast non-singular terminal sliding mode controller has been designed to achieve the finite-time trajectory tracking control of the end-effector. Furthermore, a three-fingered end-gripper mechanism has been introduced and a sub-system dynamic model consists of the end-effector and the target has been established. Based on this model, a composite compliant grasping control strategy has been designed, which is based on the compliant control theory to resolve the compliant grasping control of the end-effector towards the target. The simulation results show that the compliant capture of a tumbling target by a dual-arm space manipulator can be achieved by the proposed control strategy.

A study is conducted on the problem of achieving attitude safety control under low redundancy in micro-nano satellite. A resource efficient attitude safety control scheme is proposed, which aims to cut off all potential fault sources as much as possible when diagnostic information is not in complete. Only magnetometer and magnetic torquer are used to reconstruct the satellite attitude control system. The proposed scheme can realize angular velocity damping under any initial attitude condition of the satellite, and can control the satellite maneuvering to the sun oriented attitude, which ensures the efficiency of the solar array charging and thus extends the satellite’s lifespan under fault conditions. Mathematical simulation shows that even when the main control components such as gyroscopes, star sensors and momentum wheels are not available, the proposed scheme can still achieve stable single axis safe attitude control towards the sun, which achieves attitude determination precision by better than 2 degrees and the sun orientation precision by better than 5 degrees that greatly improves the satellite’s safety operation ability in orbit.

Under consideration of the difficulty in obtaining an accurate model of the flywheel and the limitation of computing power, a combined fault diagnosis method based on improved LSTM and fault tree is proposed. Firstly, the traditional grey wolf optimizer algorithm (GWO) is improved by population initialization, distance control parameters and α wolf position updates to achieve better convergence performance. Then, during the network training process, the improved GWO is introduced to optimize the hyper-parameter space, so the low efficiency of hyper-parameter selection caused by traditional manual adjustment method or grid search method is overcome; Further, due to considering the engineering practicality of fault tree analysis and the autonomy of neural network, a fault diagnosis framework that combines with those two ways is designed; Finally, a flywheel fault tree model is established and simulation experiments are conducted, which demonstrate the excellent convergence of the improved GWO and the effectiveness of the combined diagnosis algorithm for flywheel fault detection and recognition.

Based on the upper wind benchmark of the sounding balloon，the upper winds and the precision of corresponding maximum aerodynamic load from the wind profile radar and numerical weather prediction model forecasts from 1st day to 4th day are compared and analyzed. The results show that: the precision of the upper wind from low to high is presented by the wind profile radar and the forecast of the 4th day to the forecast of the 1st day. The precision of the wind profile radar at the altitude of 7.6 km and above is obviously low，and absolute difference is more than 5 m/s； The precision of maximum aerodynamic load from low to high is wind profile radar and the forecast of the 4th day to the forecast of the 1st day. The average absolute differences of the maximum aerodynamic load from wind profile radar and the the forecast of the 1st day to the forecast of the 4th day is respectively showed by 326.72 Pa∙rad，126.53 Pa∙rad，162.26 Pa∙rad，183.15 Pa∙rad and 212.59 Pa∙rad，and the correlation coefficient values are separately recorded by 0.76，0.98，0.96，0.95 and 0.92. Therefore，the precision of the maximum aerodynamic load from the wind profile radar is low，which cannot be used for the safety guarantee of rocket flight and needs to be further improved.

In order to achieve formation flight for unpowered aerial vehicles and ensure the convergence of formation errors in three-dimensional space， a formation control method based on consensus theory is proposed. Firstly， by taking into account the formation group's characteristics of only having negative acceleration， the consensus theory is modified， and a longitudinal control method suitable for unpowered aerial vehicles is introduced. Next， a bank angle distribution and flipping strategy is involved， and under the condition that the lift is prioritized to satisfy high-directional control requirements， the bank angle flips by the lateral error corridor， thereby both high-directional and lateral errors are simultaneously reduced. Finally， simulations are conducted to verify the adaptability of the proposed method to various formation sizes and communication topologies. The simulation results demonstrate that， within the given range of initial conditions， the proposed method can effectively control the formation in different initial states. Moreover， the initial state of the cluster has significantly impacts on formation time and cluster speed loss and average formation time and lower average cluster speed have less loss while there are clusters with more directed edges in the topology structure.

A combined navigation positioning method based on improved radial basis function neural network （RBF） assisted volume Kalman filter （CKF） is proposed to resolve reduced precision of integrated navigation positioning caused by global navigation positioning system （GNSS） signal interruption in complex environments such as tunnels， urban roads and canyons. Firstly， the integrated navigation fusion data is preprocessed by using kernel principal component analysis （KPCA） combined with K-means++ clustering model to make its distribution representative； Secondly， the orthogonal least squares （OLS） method is used to determine the number and center values of hidden layer neurons in the RBF neural network， and the trust region constrained Gaussian-Newton （TR-CGN） algorithm is used to optimize its parameters； Finally， when the GNSS signal loses lock， the trained improved RBF neural network is used to assist in nonlinear CKF filtering for error compensation. The experimental results show that the average positioning error is reduced by 17.87% through application of this method without increasing hardware costs which is compared to the way of using the autonomous driving collaborative positioning system； Compared with the average positioning error assisted by KPCA-RBF， the reduction based on the proposed method takes advantage of 54.37%， which indicates that the adaptability and robustness of the integrated navigation positioning system are effectively enhanced within complex environments.

A hybrid control method combining feed-forward compensation with closed-loop feedback based on the target relative motion trajectory is proposed in this paper, which is aiming at significantly improving the satellite dynamic pointing tracking control precision. Firstly, the dynamic error coefficient method is adopted to analyze the attitude tracking errors, and power transfer function is established to analyze attitude angular velocity errors caused by sensor noise. Next, a feed-forward compensation control strategy calculating the desired line-of-sight angular velocity and angular acceleration by estimation of the target relative motion is proposed, which resolves the challenge of space-borne detection equipment that can only measure target pointing deviations and doesn’t directly perform hybrid control. Finally, the system stability and attitude tracking performance are validated through mathematical simulations, and ground-based air-bearing experiments are implemented to test the controller's tracking performance. This attitude controller reaches high-precision during dynamic tracking by different input commands without altering the closed-loop feedback bandwidth.

Regarding the planning of on-orbit refueling tasks for spacecraft in geosynchronous orbit (GEO), an on-orbit refueling strategy based on hierarchical refueling is proposed, which can effectively improve the refueling efficiency compared with the traditional “one-to-many” refueling method. In the proposed hierarchical on-orbit refueling strategy, a sub-service spacecraft (SSc) is defined to jointly accomplish the on-orbit refueling task with the primary service spacecraft (PSSc). On the basis of this, the spacecraft orbital transfer model based on the multi-turn Lambert orbital transfer, the relationship between orbital maneuvering speed increment and transfer time is obtained, and the fuel cost and transfer time of spacecraft orbital transfer are taken as the objective function under consideration of the constraints such as spacecraft load and mission time, and the spacecraft refueling sequence and orbital transfer time are optimally solved by using an improved genetic algorithm. Finally, the effectiveness of the theory is verified through numerical simulation.

On account of the issue that the communication network of multi-flight vehicles is vulnerable to be attacked by false data injection in the disturbance environment， a collaborative guidance strategy against high-speed targets that can autonomously identify and suppress the fault link is proposed. By designing the coordinated guidance method based on relative distance， when only the leader flight vehicle can get the target movement information， the flight vehicles can hit the maneuvering target at the specified time. The radial basis network is used to estimate the unknown items for the design of cooperative guidance law. The trust coefficient is introduced to identify the false data injection attacks on the communication network， which guarantees the information assurance for self-suppression of the multiple flight vehicle systems under the network attacks.The numerical simulation result indicates that the leader and followers multi-vehicle collaborative impact on the high-speed target simultaneously can be controlled and implemented by using the proposed method under the false data injection attacks.

In order to solve the path planning of unmanned aerial vehicles (UAVs) in three-dimensional space under threats, an improved snake optimization (ISO) algorithm is proposed for the challenging optimization of UAVs path planning in three-dimensional complex environments. Firstly, the total cost function including range, threat, altitude and smoothing costs is established, and the path planning of UAVs is transformed into an optimization issue that takes into account the safe operation requirements of UAV. In the framework of snake optimization (SO), Tent chaotic map is used to initialize the population, and the temperature threshold is dynamically adjusted to improve the local optimization ability of the algorithm, and Lévy flight strategy is introduced in the exploitation phase to improve the global optimization ability of the algorithm. The simulation results show that the ISO algorithm is superior to the SO algorithm by solving the path planning of UAVs.

In order to achieve high-speed data transmission between the user satellite antennas and relay satellite, single channel monopulse tracking systems are used to realize high-precision tracking. The design of auto tracking system based on integration of Ka-band tracking receiver and Servo controller is described in this paper, where TE21 mode coupler is used on Ka-band antenna. Tracking receiver model is established on the nonlinear dynamics model. Auto-tracking pointing error is provided by the model. Comparing the simulation with experiment results, the math model is correct and reliable. The Auto-tracking system is test on far-field. Tracking receiver’s S curve, dynamic performance and pointing error are applied to test. The experiment results demonstrate the auto-tracking system function and performance meets the requirements of task by precision pointing.

In response to the complex and uncertain conditions faced by solar sail spacecraft during in-orbit flight, a deep reinforcement learning-based integrated algorithm for trajectory design and robust guidance is proposed. The uncertainties conditions acted as solar radiation pressure model uncertainty, navigation error, control execution error and randomly triggered safety events are incorporated into the Markov decision process modeling of solar sail spacecraft in-orbit flight, based on the algorithm proposed regarding orbital dynamics of solar sail spacecraft. A reward function reflecting the optimization of solar sail energy supply is designed by the minimum solar phase angle, and training is conducted by using the proximal policy optimization algorithm to achieve the optimization design of solar sail spacecraft trajectories and robust guidance under complex and uncertain conditions. This algorithm is applied to the heliocentric transfer mission of a solar sail spacecraft exploring the near-Earth asteroid 2019 GF1. Simulation results show that the terminal arrival precision of nominal trajectory tracking flight under uncertain conditions can be decreased and the solar phase angle along the trajectory is reduced by using this new algorithm.