An aerospace evolutionary control system is proposed. Firstly， combining typical scenarios and the challenges faced， and the theoretical basis and research significance of evolutionary control system are specified. Then， by starting from basic concepts， a comprehensive definition of evolutionary control systems is established， and their key characteristics are deeply analyzed. Moreover， in order to realize implementation， discussions are conducted from the two dimensions known as design objectives and development planning. In addition， the specific schemes for transferring evolutionary control systems into practical applications are proposed. Finally， comprehensive explorations and practice are conducted from the two perspectives of technology development and equipment application towards this system.
New-type missiles designed for attacking maritime surface targets are key strike forces in modern naval warfare， which impacts on the balance of maritime power through the evolution of their flight speed， guidance methods and penetration capabilities has exerted a profound influence on the balance of maritime power. A systematic review on the technological progression of such missiles development from subsonic and supersonic systems to emerging hypersonic grade， and key technologies are examined from multiple perspectives， including propulsion systems， blackout-mitigation techniques and advanced flight control methods. Furthermore， the development trends of multi-source information fusion， intelligent mission assessment and cooperative strike operations are focused， which are expected to shape the future trajectory of maritime surface-attack missile systems.
A disturbance observer-based adaptive fuzzy model predictive control method is proposed to solve the attitude control difficulty of quadrotor UAVs in complex environments. A nonlinear dynamic model of the quadrotor UAV is established， including external disturbances. In order to effectively handle system nonlinearities and constraints， the T-S fuzzy modeling approach is employed to transform the nonlinear model into a set of local linear models which are then embedded into a model predictive control framework for rolling optimization solution. Meanwhile， an adaptive prediction horizon adjustment strategy is designed to dynamically optimize controller parameters， which is based on the system's dynamic characteristics to optimize controller parameters in real time and effectively balances dynamic response speed and robustness. Furthermore， by establishing a Lyapunov function， stability analysis of the state equations is conducted， rigorously proving the asymptotic stability of the system under this adaptive strategy. The simulation results demonstrate that outstanding stability control capability and strong robustness performance is presented by applying proposed method in complex uncertain environments.
Aiming at the attitude control of reusable launch vehicle in reentry phase under restrains of parametric uncertainties， external strong disturbances and compound actuator faults， an adaptive sliding mode fault-tolerant control method based on composite disturbance observer （CDO） is proposed. Firstly， the RLV attitude tracking error model considering actuator effectiveness loss and bias faults is established. Then， a cascade and fused CDO is designed to accurately estimate the lumped disturbance. On this basis， a chattering-free adaptive sliding mode control law based on the disturbance compensation strategy is designed， which employs the online adaptive gain to replace the discontinuous switching subject and ensure fixed-time convergence while eliminating chattering. The simulation results show that compared with existing methods， the tracking accuracy， convergence speed and control smoothness are significantly improved by using the proposed scheme which is under fault scenarios with extreme disturbances and verifies its superior fault-tolerant performance and robustness.
Regarding the investigation of a cluster of flight vehicles by using multi-stage solid rocket boosters， the research is implemented for the collaborative trajectory optimization. In order to facilitate the collaborative task during the re-entry phase and ensure the optimum energy performance of the cluster by eliminating individual state errors， a multi-layer collaborative trajectory optimization algorithm is proposed， which is based on the hp adaptive pseudo-spectral method. By designing different planning models in the top， middle and bottom layers， the algorithm achieves time-coordinated reentry. Firstly， a trajectory planning model is established， which is based on the flight characteristics of the booster phase， and sparse collocation points are used to determine the cluster's temporally coordinated interval. Then， the single-vehicle planning model is extended in dimension， and after introducing constraints on the rate of change of control variables， the hp adaptive pseudo-spectral method is applied to quick resolving for the desired terminal state. Finally， additional collocation points are incorporated for refined optimization. Simulation results demonstrate the effectiveness of the proposed method by enabling rapid and effective optimization of the flight vehicle cluster， which meets the requirements for collaborative trajectory planning.
In order to achieve the synergy between periodic self-operation control and task-driven non-periodic random control， an intelligent attitude control method is proposed for launch vehicles， which is based on reinforcement learning model predictive control （RMPC）. Firstly， a break point identification method based on time-frequency analysis is established to address the issue of switching requirements between periodic orbit maintenance and non-periodic maneuver adjustment during rocket flight. By monitoring the spectral characteristics of control command sequences in real-time， the transition boundary between periodic and non-periodic time processes is accurately located， which can serve as decision-making basis for control mode switching. Secondly， a RMPC framework integrating adaptive attention mechanism is proposed， which can dynamically adjust the prediction model structure and iterative optimization steps based on fuzzy neural network according to the type of control task， while ensuring prediction accuracy and controlling model complexity. Finally， an environment aware time-domain decision-making method is designed to enhance the adaptability of RMPC in complex environments by adaptively adjusting the predicted and control time domain lengths through online evaluation of external interference strength and system state uncertainty. The method is applied to closed-loop control simulation of typical flight scenarios of launch vehicles， and the experimental results show that trajectory tracking control precision can be maintained by using the proposed method in both periodic orbit maintenance phase and non-periodic maneuver phase.
A kind of line-of-sight（LOS） rate strapdown decoupling method of phased array radar explorer vehicle is proposed in this paper. Based on the relative motion relationship between target and flight vehicle in the target coordinate system， the second-order nonlinear model of the LOS angles and rates in the polar coordinate is derived， and the rates of LOS angles and the change rates of relative distance is estimated by using the method of extended Kalman filter. The simulation and comparison results show that the decoupling method can effectively isolate the deviation of reconfiguration LOS angles in target coordinate caused by the attitude errors， and can accurately acquire the LOS angle rates for guidance and enhance the arrival precision of flight vehicles. The method is simple for the engineering implementation and can serve as fairly good reference in the current flight vehicle field.
In order to solve the UAV path planning problem under complex threat scenarios， an improved hybrid intelligent optimization algorithm termed HGWOSCA is presented， which synthesizes the merits of the grey wolf optimizer （GWO） and the Sine Cosine algorithm （SCA）. The algorithm's performance of globe search ability and partial development precision is significantly improved through the integration of a Circle chaotic initialization strategy， a nonlinear oscillation control parameter a， and an piecewise Sine selection strategy. On this basis， a mathematical model adaptive to UAV trajectory planning is developed， and cubic spline interpolation is applied to smooth the generated trajectories， thereby their feasibility and adaptability are enhanced. Simulations are conducted in comprehensive scenarios under varied threat conditions to validate the algorithm's performance. Experimental results confirm that HGWOSCA consistently has better performance than seven benchmark metaheuristic algorithms through all test scenarios， which shows fairly good robustness and superiority.
In response to the environmental adaptability analysis challenges which arise due to flexible electronic technologies applied to aerospace， a study is conducted on simulation methods for space environment adaptability of hybrid integrated circuits based on flexible chips. Firstly， combined with the characteristics of flexible hybrid circuits， weak objects in the environments of bending stress， thermology and mechanics are targeted. A multi-dimensional selection of flexible chips， packaged devices and flexible circuit boards is made for modeling and simulation method research. Subsequently， this method is applied to simulation analysis on a kind of flexible hybrid circuit， and the simulation results are used to guide the design and optimization of the circuit. The research results indicate that this method has guiding significance for initially assessing the performance of flexible integrated circuits in complex space environments， which lays a foundation for promoting the application of flexible electronic technology in aerospace industry.
Addressing the issues of challenge for balancing fuel economy， bus voltage stability and battery lifespan in energy management strategies for turbo-electric hybrid vertical takeoff and landing （VTOL） UAVs， a component-level simulation model of the hybrid power system is established， which incorporates a turbine generator system， battery energy storage system， three-level rectifier and bidirectional DC/DC converter， and a kind of two-layer model predictive control （MPC） energy management strategy is proposed. The upper-layer MPC is targeted for optimization by minimized fuel consumption， and generator output constraints， state-of-charge （SOC） variations and battery degradation factors are combined in order to achieve multi-timescale power forecasting and dynamic allocation. The lower-layer MPC focuses on DC bus voltage stability， employing duty cycle control of the bidirectional DC/DC converter for rapid voltage regulation. Simulation verification is implemented under typical long-endurance and pulsed-load composite operating mode in offshore flight environment， which demonstrates the strategy's significant advantages of enhancing energy efficiency， reducing battery life degradation and improving system stability.
To address the issue of requirements for efficient processing and precise decision-making of multi-source heterogeneous fault data during implementing modern aerospace missions， a large-language-model-based aerospace equipment fault scheme is proposed， which follows agent architecture to build a four-layer closed-loop system of "data-knowledge-decision-application" that integrates core functions such as fault process mining， historical case matching， process node response and plan report generation. In terms of technical realization， a two-stage mining algorithm based on process intermediate representation is used to extract the structured disposal process， historical cases are associated through combining BM25 with semantic vector hybrid matching algorithms， and knowledge graph embedding technology is relied to achieve semantic alignment of faults and process nodes， and the automation driven fault disposal plans is ultimately generated. This architecture is verified in a leakage current scenario within the control system of a launch vehicle. The intelligence and standardization level of fault handling is significantly improved and presented technical support can serve for rapid response to aerospace equipment fault plans.
The sneak circuits in two grounding designs for launch vehicle electrical systems： a grounding shell and a floating ground-grounding shell are analyzed， and the sneak circuits are presented in both designs. Based on electromagnetic field theory， a sneak circuit model is established for the launch vehicle electrical system grounding system under transient high voltage and electromagnetic radiation conditions. The impact of transient high voltage and electromagnetic radiation on the operation and failure phenomena of the launch vehicle electrical system is analyzed theoretically. Based on the sneak circuit model， grounding design principles are proposed for both grounding schemes， which suppress sneak circuits in the electrical system. The analytical approach and methods presented in this paper can serve as a reference for other designers and the reliability and robustness of launch vehicle electrical systems can further be improved.
