Regarding the focused security requirements of test launch and control system in authentication and authorization， data security protection and traceability of abnormal operations， researches are conducted on the application of blockchain technology in authentication and authorization management. The design of network architecture， account information model， consensus mechanism and differentiated authorization smart contract algorithm are elaborated in this paper， which is verified through the simulation by using self-developed measurement and control network blockchain authentication and authorization platform.

Aiming at full system test data and career information， environmental data， etc of multiple source and huge heterogeneous data of aerospace equipment， a data-based health management system is developed，which achieves the integration and storage management of test data，product career data，environmental data， model analysis and health assessment.The system is developed through service-oriented architecture design， which is based on information gathering and processing for realizing integration and management of equipment test data and takes advantage of high-reliability test data storage and management foundation using lightweight distributed column storage mechanism.Regarding the health status of the system and key units， the trend analysis，life prediction， maintenance decision information and hierarchical situation presentation， which are based on algorithm models，are introduced. Realization of the health status evaluation，health trend analysis，life prediction，maintenance decision support，etc for the full system and key units can be served as a reference of equipment data health management solution.

As a critical factor affecting safety-critical systems， it has been drawn increasingly attention to software safety issues. Based on engineering practices in aerospace embedded software testing and verification， the software safety requirements are taken as a clue and typical safety problems are focused in this paper. The two dimensions are introduced by the formal verification of source code safety properties and the automated testing of software safety requirements which analyze and summary key technologies， including special safety analysis， source code static analysis， source code model checking， fault-model-based safety testing and keyword-driven automated testing. A comprehensive technical solution for aerospace embedded software safety verification is proposed， and an independent controllable software assurance support platform and tools are developed to systematically enhance the trustworthy assurance capabilities of aerospace embedded software.

Aiming at the current situation of tight software-hardware coupling， large scale and high complexity in the test and launch control system of aerospace equipment， a layered decoupled software-defined test and launch control system architecture is proposed. Through taking advantage of middleware technology， the hardware resources of test and launch control system are highly integrated and abstracted， and application-oriented software is enabled to dynamically load and reconstruct components based on users' requirements. The proposed architecture has the features of hardware-on-demand expansion and flexible high extensibility of software， which improves the utilization rate of test and launch control system resources， task flexibility and system reliability.

Aiming at the shortage of existing fault diagnosis methods for in-orbit satellites， a satellite fault diagnosis system based on Clips expert system is proposed in this paper. The satellite fault is diagnosed in real time by taking advantage of existing satellite fault knowledge and experience， combining expert experience with real-time telemetry data and using inference machine technology. At the same time， expert knowledge is input and edited by visualization technology including graphics and knowledge expression. The expert knowledge base is established to transform the simple logic statements that is easy to be understood by users into complete and complex Clips statements to realize complex fault diagnosis programs， and it is going on to realize the automation and intelligence of real-time fault diagnosis of spacecraft in orbit， accurately locate faults and improve the reliability and safety of satellite systems. Through multi-domain simulation of multiple fault scenarios and project practice， the diagnosis results of the satellite fault diagnosis system are the same as the actual fault data received by the satellite， which verifies the effectiveness of the designed system.

A hybrid optimization method based on deep neural networks is proposed in this paper for the spacecraft pursuit-evasion game problem with free terminal time and {\mathrm{J}}_{\mathrm{2}} perturbation considerations. Firstly，the data set is generated by solving the two-point boundary value problem without {\mathrm{J}}_{\mathrm{2}} perturbation using traditional optimization algorithms. Then， on the basis of that， a deep neural network is established to fit the relationship between the initial state and the solution， and the initial guess solution is generated. Finally， the solution is further optimized by using a local optimization algorithm. Through simulation and verification， it is demonstrated that this method not only performs good feasibility and robustness but also significantly improves computational efficiency， which is compared with traditional hybrid optimization algorithms.

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.

An adaptive sliding mode control strategy based on the randomized feedforward neural network is proposed for the path tracking control problem of heavy-load quadrotor unmanned aerial vehicle （UAV） affected by model uncertainties and external unknown disturbances. The dynamics system of heavy-load quadrotor UAV is experienced by the model uncertainties and external unknown disturbances during flight which are defined as the lumped disturbance term. By taking advantage of randomized feedforward neural network， the lumped disturbance term in each channel is adaptively estimated and then used to compensate the adaptive sliding mode controller. Based on the Lyapunov stability analysis method， a rigorous proof of the convergence of path tracking errors for heavy-duty quadrotor UAV is presented. The effectiveness of the proposed control method is fully verified by the simulation results.

Aiming at the stability control of a slender air defense missile under low elastic frequency and multiple constraints， a linear time-varying model predictive control method which is considered under elasticity and multiple constraints is proposed. Firstly， in order to ensure the amplitude attenuation in the mid-frequency band， the overload error integral output is used to augment the missile's linear state space equation. Under the model predictive control full state feedback strategy， the controller inherits the structure of the traditional three-loop control method. Then， a cost function is established， which is based on the criterion of ensuring the rapidity and smoothness of the missile's overload and attitude response， and the missile's stability control problem is transformed into a rolling optimization solution of model predictive control. Finally， in order to ensure the stability and elastic suppression capability of the system under elastic working conditions， a notch is inserted into series at the output end. The simulation results show that the proposed method has faster response speed， higher control accuracy and better elastic suppression ability， compared with the traditional three-loop control method.

Aiming at the obstacle avoidance of multiple quadrotor UAVs in complex and variable wind fields， a aimed trajectory planning algorithm based on Gauss pseudo-spectral method （GPM） is proposed to solve the obstacle avoidance of multiple quadrotors in mixed wind fields. Firstly， a dynamic model for a single quadrotor in a mixed wind field is established. On the basis of this， the constraints on the wingmen in the formation are transformed into constraints on the leader， thereby a multi-constraint trajectory planning model is established. Under the premise of ensuring that the formation can reach the target location on time， this model minimizes the energy consumption required for formation flight is minimized by using this model regarding the optimization objective. The GPM is utilized to optimize the trajectory of the leader， which is then formulated as a nonlinear programming problem （NLP）. The sequential quadratic programming （SQP） algorithm is adopted to solve this problem， which yields an optimal flight trajectory that satisfies both the constraints and the optimization objective. Simulation results demonstrate that the proposed method enables multiple UAVs to safely navigate around obstacles within mixed wind field environments and generate optimal flight trajectories while satisfying the constraints.

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 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.

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.

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.

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.

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.

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.

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.

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.

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 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.

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.

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.

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 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.

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.

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.

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.

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.

Aiming at the problem that magnetometer or sun sensors can only estimate the attitude of two axes, the observed quantity is presented by using the method of taking advantage of the observation vector measured by sun sensors and magnetometer, the attitude error is gained by using sun vector which is compared with the geomagnetic field vector estimated based on the orbit and the attitude angular velocity of the satellite. The integrated attitude of the gyro is corrected by the attitude error estimated based on the sun vector and the geomagnetic field vector, and the gyro drift is estimated based on PI filter. The simulation result shows that the attitude determination precision reaches about 1°.