Aiming at the problem that the online trajectory planning of high-speed unmanned aerial vehicle（UAV） in the ascending phase needs to realize online fast solution under multiple constraints, firstly, the motion and dynamics model of the vehicle was built, and the constraints faced by the trajectory planning were given. According to the constraints and flight characteristics, the action state space and reward evaluation function that meet the mission requirements were designed based on the near end strategy optimization（PPO） strategy gradient optimization. Secondly, based on the characteristics of strong time memory of the trajectory planning in the ascending phase of the aircraft, the short and long term memory network（LSTM） network structure was introduced on the basis of the traditional PPO algorithm, and the PPO-LSTM algorithm was used to solve the online trajectory planning problem in the ascending phase of the high-speed aircraft, and the model that can plan the optimal angle of attack strategy in real time according to the aircraft state was trained. Finally, the performance of the algorithm was verified by Monte Carlo simulation. The results show that the root-mean-square error of the terminal state of the algorithm in this paper is reduced by about 50% compared with the traditional PPO and particle swarm optimization,which fully proves the superiority and effectiveness of the proposed algorithm.

[Objective] The hybrid unmanned aerial vehicle（UAV） has become an important technical means in the UAV field because of its excellent lift-drag characteristics and endurance. The endurance of an UAV can be improved mainly by obtaining good lift and drag characteristics and reducing its weight. Using a modular UAV as the research object, this paper established a hybrid UAV configuration concept, mainly considering the stress change rule and the maximum fatigue life of the monomer UAV under aerodynamic force, and its lightweight design goals under the fatigue life and the maximum stress constraint. [Methods] This paper conducted research on lightweight design mainly in three ways: 1) According to the hybrid UAV concept, an overall configuration of “main body + monomer” is proposed and the full-text research object is provided. The monomer UAV is an important task-combined UAV unit, so the mechanical properties of every single part and the overall topology structure are emphasized. 2) In the incompressible unsteady three-dimensional continuous equation and Navier-Stokes（N-S） equation, momentum analysis is carried out on the aerodynamic characteristics of a single wing UAV in a full working environment, the regional flight parameters are clarified, and the maximum aerodynamic force is selected as the ultimate load, in the form of loading a sine function into the single wing. The monomer stress distribution of the maximum stress region of the wing-body is extracted. Combined with Fe-safe numerical analysis software, fatigue life analysis is performed, and improvements are proposed for sensitive areas. Based on the service life guarantee and the solid isotropic microstructure with the penalization（SIMP） method, a topological optimization analysis of a single wing, load-bearing frame is performed. 3) A monomer wing finite element model is established to verify the correctness of the topology optimization model. For a single wing, all the structural analyses of the static and dynamic analysis results verify the correctness of the above theoretical analysis. At the same time, in the topology analysis link, because each tolerance beam differs in weight, analysis was performed for each beam. [Results] In this paper, based on the classic SIMP topology optimization method, the topological calculation and analysis of the single wing’s front beam, middle beam, rear beam, and middle rib show that the weight of each beam is reduced by 5%, 10%, 5%, and 15%, respectively, under the premise of invariable mechanical distribution. After obtaining the analysis results, the weight of the entire wing is reduced by 35%. an innovative topology optimization process is adopted to analyze the fatigue life of key parts before the wing is joined, ensuring the process optimization of the wing and the service life of key parts. The proposed method integrates key position optimization, topology optimization, and fatigue life analysis, avoiding separate post-assembly fatigue analysis of key positions, optimizing the whole analysis process, and improving the work efficiency of lightweight analysis. [Conclusions] The wing topology optimization method under the fatigue life constraint proposed in this paper reduces the weight of a single UAV by 35% under the condition of constant force and improves the efficiency of wing lightweight analysis. The new analysis method provides technical support for subsequent UAV optimization analysis.

This article proposes a novel 3-D sliding mode interception guidance law for maneuvering targets, which explores the potential of reinforcement learning (RL) techniques to enhance guidance accuracy and reduce chattering. The guidance problem of intercepting maneuvering targets is abstracted into a Markov decision process whose reward function is established to estimate the off-target amount and line-of-sight angular rate chattering. Importantly, a design framework of reward function suitable for general guidance problems based on RL can be proposed. Then, the proximal policy optimization algorithm with a satisfactory training performance is introduced to learn an action policy which represents the observed engagements states to sliding mode interception guidance. Finally, numerical simulations and comparisons are conducted to demonstrate the effectiveness of the proposed guidance law.

临近空间飞行器在稀-稠大气过渡阶段且反推力矢量装置(Reaction Control System,RCS)有剩余燃料的情况下,RCS对于非冗余舵面的故障补偿与在线重构具有重要意义.基于此,研究了针对非冗余舵面与RCS复合故障的自愈控制方法,以实现飞行器的安全可靠控制.首先,建立了执行机构故障等不确定影响下的姿态控制模型;其次,针对舵面故障给出了基于残差观测的故障检测与自诊断方法,设计了 RCS与舵面复合故障的分离诊断策略;然后,基于非线性比例-微分控制及故障诊断信息,设计了舵面故障补偿的自愈控制器;同时,基于 RCS故障喷管序列判定,设计了复合故障下 RCS在线重构的自愈控制器.最后,通过某典型全弹道姿态跟踪数值仿真,验证了该方法的有效性及可靠性.

In this paper, constraints of actuator amplitude and rate are taken into consideration for near-space vehicle (NSV). Based on the second order actuator dynamic model and the dynamic of NSV, the control model for NSV with actuator dynamic is presented. Thus, the constraint on actuator amplitude and rate are translated into states constraints. By utilizing the barrier Lyapunov function (BLF) handle state constraints, a novel control scheme based on dynamic surface control is constructed for NSV with actuator amplitude and rate saturation. The stability analysis illustrate that the closed-loop system is stable, and the actuator amplitude and rate never violate the constraints. Nonlinear simulation is presented to demonstrate the performance of the control scheme.

Aiming at the problem of poor trajectory adaptability, low guidance accuracy and not suitable for the airbrake failure in the traditional terminal area energy management (TAEM) algorithm, an intelligent online planning scheme for TAEM 3-DOF trajectory is proposed. Firstly, a 3-DOF trajectory defined by three parameters is designed according to the constraints of the aircraft; Secondly, a strategy of TAEM trajectory online planning is proposed, which uses the idea of predictor-corrector and takes the velocity deviation as the feedback to iterate the three parameters of trajectory online. Finally, a scheme of online aerodynamic parameter intelligent identification is designed by using the advantages of RBF neural network, such as strong generalization ability, fast learning convergence speed and high accuracy. Combined with the above trajectory online planning algorithm, the comprehensive management of aircraft altitude and velocity is realized under the condition of strong uncertainty and airbrake failure, and the robustness and adaptability of the trajectory are enhanced. Under the PD guidance law, the simulation results show the feasibility, rapidity, and strong adaptability of online intelligent trajectory planning algorithm.

针对放宽静稳定度条件下水平起降空天飞行器控制舵面尺寸设计难度大的问题,提出了一种基于代理模型的控制舵面一控制参数一体化设计方法.首先,基于鸽群算法构建了包含结构参数的空天飞行器气动特性代理模型,获得了气动特性参数随飞行条件、控制舵面尺寸及质心位置的变化关系,为控制舵面一体化设计提供输入.然后,设计了基于C*结构的空天飞行器纵向参考模型跟踪控制律,并将考虑飞行品质约束的空天飞行器控制舵面一体化设计问题转化成多约束条件下的多目标优化问题.并采用非光滑优化算法计算得到了同时满足飞行品质、舵面饱和、舵面偏转速率等约束的最小控制舵面及对应的控制参数.仿真结果表明,该方法能够在满足性能指标约束的前提下有效减小控制舵面的尺寸,具有较强的工程应用价值.

针对空天飞行器再入制导问题,提出一种考虑禁飞区规避的分段预测校正制导方法.在再入段前期采用剩余航程作为目标函数,后期引入预测落点偏差作为目标函数进行制导指令求解,同时确定倾侧角幅值和符号,兼顾了计算效率与终端制导精度.在此基础上,对于再入过程中的禁飞区规避问题,把禁飞区分为两类,增加了通过倾侧角幅值修正策略实现侧向规避制导的逻辑,可适用于无法单独通过倾侧角反转规避禁飞区的情况.最后,通过开展考虑再入初始状态和气动品质不确定性的蒙特卡罗仿真,验证了提出的分段预测校正制导方法可以有效引导空天飞行器规避禁飞区,与单段目标函数预测校正方法相比,具有更高的制导精度.

针对空天飞行器无动力着陆轨迹设计问题,提出一种椭圆式高度剖面的离/在线轨迹设计方法.传统设计方法在参考航天飞机轨迹设计方法的基础上进行优化改进,但避免不了设计过程中参数繁多、连续性较差等缺点,并且不能够在飞行器着陆过程中在线更新轨迹以保证着陆精度.以往的在线轨迹设计方法计算量大、对机载计算机的计算能力要求较高.提出的设计方法克服了传统方法的缺点,在满足各项指标要求的同时更具有连续性与平稳性,并且该方法简单、快速,适用于飞行器在线生成轨迹.

针对可重复使用空天飞行器的再入及返场问题,通过设置航路点开展了分段预测校正再入制导方法研究.首先,在发射坐标系下建立了动力学模型,对再入过程中的约束条件进行了分析与转化;其次,给出了数值预测校正制导方法的设计逻辑,针对该算法迭代中可能产生的发散问题与饱和问题,一是引入一个调节因子来自适应地调整迭代步长,二是为迭代设置与速度相关的误差限,三是采用了设置航路点的方式对再入过程分段,缓解了气动不确定性带来的影响,完成了数值预测校正方法的改进;最后,通过对某空天飞行器的数值仿真验证了该方法的有效性,使用航路点分段策略能够进一步消除制导指令饱和,提升制导精度.

The control system design for the reusable launch vehicles (RLVs), especially in the autonomous horizontal takeoff phase, is a highly challenging task. Significant issues arise due to the high nonlinearity, large uncertainties of aerodynamic coefficients as well as strong coupling among axes of the airframe. This paper studies autonomous takeoff control problem of the RLVs by the means of trajectory linearization control (TLC) and model predictive control (MPC) theory. The six degree of freedom dynamic model is firstly established, and the flight strategy of takeoff and climb stage is provided through the characteristic analysis of RLVs. Furthermore, the guidance law for the climbing phase is proposed via the TLC method against the high nonlinearity, and a speed based gain-schedule strategy is given under the consideration of both aerodynamic force and friction force. In order to eliminate the ground effect interference, an improved model predictive control approach is presented by introducing the online parameter estimation of the ground effect interaction coefficient, and a coupled model predictive controller is designed by introducing the feedback of sideslip angle into the roll control channel to eliminate the coupling effect. Finally, the performance of the design method for autonomous takeoff control of RLVs is demonstrated through the comparison simulation analysis.

针对升力式飞行器再入制导问题提出了一种智能预测校正制导方法.首先,以数值预测校正制导为出发点,考虑预测环节计算时间过长的问题,通过引入神经网络航程估算模型代替动力学积分过程,快速计算剩余飞行航程.然后,为了进一步降低神经网络训练数据规模,分析了飞行状态参数对剩余飞行航程的影响规律,对神经网络的结构进行了优化,设计了用于航程估算的全连接神经网络模型.最后,将训练好的神经网络模型应用于再入制导前中期,结合分段目标函数设计,在再入后期使用等距试探确定制导指令.蒙特卡罗仿真结果表明,所提出的基于神经网络航程估算模型的预测校正再入制导算法具有良好的鲁棒性,在保证精度的前提下提升了计算效率.

对水平起降两级入轨(TSTO)运载器一子级返场轨迹优化和轨迹在线生成问题进行了研究.首先,给出了较独特的一子级再入轨迹设计策略:先给定侧向剖面,再分段优化求解三维轨迹.针对返场过程的大幅转向需求,设计了形式简单的倾侧角-航向角偏差剖面,并定义了具有不同任务的航向转弯段和航向微调段;针对一子级宽速域气动变化显著特点,为避免轨迹跳跃,定义了增高减速段和下降滑翔段,并采用分段优化策略求解三维轨迹.其次,针对分离扰动造成的一子级初始状态偏差,扩展了自适应高维伪谱插值(AMPI)算法的参数空间,并将其应用于返场轨迹在线生成问题.仿真结果表明,设计的倾侧角剖面能够在倾侧角不翻转的前提下调整飞行航向对准着陆场,设计的分段优化策略能够保证高度曲线平稳无跳跃,采用的自适应高维伪谱插值算法能够在分离扰动影响下快速准确地实现在线轨迹生成.

针对涡轮/冲压/火箭三组合动力水平起降高超声速飞行器爬升段飞行轨迹设计和制导律设计问题,首先考虑宽速域组合动力发动机多模态特性和高低速气动特性差异,分别开展了涡轮段、引射段、纯冲压段及冲压火箭段的飞行策略研究,提出了不同阶段的飞行攻角剖面构型和火箭流量剖面构型,将无穷维轨迹优化问题转化为有限维参数规划问题,进而完成了组合动力上升段飞行轨迹的优化设计;在此基础上,结合轨迹线性化控制方法,开展了组合动力上升段轨迹跟踪制导律设计研究,给出了保证闭环稳定性和控制品质的制导律参数设计准则,最后通过开展仿真分析说明了提出轨迹设计及制导方法的有效性.

This paper studies the reentry attitude tracking control problem for hypersonic vehicles (HSV) equipped with reaction control systems (RCS) and aerodynamic surfaces. The attitude dynamical model of the hypersonic vehicles is established, and the simplified longitudinal and lateral dynamic models are obtained, respectively. Then, the compound control allocation strategy is provided and the model predictive controller is designed for the pitch channel. Furthermore, considering the complicated jet interaction effect of HSV during RCS is working, an improved model predictive control approach is presented by introducing the online parameter estimation of the jet interaction coefficient for dealing with the uncertainty and disturbance. Moreover, considering the strong coupling effect between the yaw channel and roll channel, a coupled model predictive controller is designed by introducing the feedback of sideslip angle into the roll control channel to eliminate the coupling effect. Finally, the comparison simulations using the classical control method, MPC and IMPC approach are given to demonstrate the effectiveness and efficiency of the presented IMPC scheme.

Ordinary the control system of the aerospace vehicle (ASV) is designed basing on itself linear system. However, there are some non-linear parts in the actuator which can effects flight attitude control. Using the methods of analyzing linear system cannot identify the factors influencing the control system. This paper use description function to analyze the effects for control system. On that basis, this paper put forward a new approach which changes control system by adding series leading correction and reducing gain. Meanwhile, this article proposed an optimal design scheme considering nonlinearity of ASV.

Principal component regression (PCR) is not only a kind of multivariate statistical method, but also a type of data-driven method. The improved PCR (IPCR) optimizes the performance of fault detection for Tennessee Eastman process (TEP). IPCR could solve the unsatisfactory detection performance generated by the incomplete sample decomposition. Multiple IPCR (MIPCR) is a novel improved method relative to IPCR. It uses multiple quality variables to detect product quality at the same time. And the results, obtained via MIPCR, are fused. Then screening the variables via the fault performance is done. Simulations for Tennessee Eastman process (TEP) are presented with PCR, IPCR and MIPCR. Via the simulations, the validity and superiority of MIPCR are all verified.

The numerical predictor-corrector re-entry guidance algorithm is proposed for aerospace vehicles(ASV). Firstly, over the spherical rotating Earth, the three degree of freedom dynamical model of ASV is established in the launch coordinate system and the trajectory constraints are analyzed for the re-entry phase. Then, the predictor-corrector entry guidance algorithm numerically computes a complete entry trajectory onboard repeatedly based on the current state and required targeting condition, and the required bank angle command can be computed by the selected iterative algorithm to achieve the guidance accuracy. Simultaneously, a bank reversal logic is given by online prediction of the cross-range for the lateral guidance. Moreover, in order to avoid the numerical divergency problem at the end of re-entry phase due to the range-to-go tends to zero, the total re-entry range is used to replace the range-to-go in the corrector algorithm, particularly the adaptive iterative algorithm is employed to guarantee the convergence and accuracy of the predictor-corrector guidance algorithm. Finally, numerical simulations have been carried out to test the validity of the proposed entry guidance algorithm. The simulation results demonstrate that the re-entry guidance works well and has a good performance.

As various faults are inevitable during a satellite’s on-orbit operation, a modified intermittent process performance monitoring method is proposed. This performance monitoring of a satellite is performed via attitude information. This method not only overcomes the defects of the traditional intermittent process methods of requiring a priori knowledge and the difficulty in handling points on adjacent edges but also reduces the defects, such as omissions and false positives caused by the process modeling. This method combines the multiphase auto regression principal component analysis monitoring method based on affine propagation clustering (APC) optimized, and at the meanwhile, the population diversity-based particle swarm optimization algorithm is considered in APC. Numerical simulations proved the effectiveness of the proposed approach.

A method of attitude stabilization control, based on observer design is proposed for an on-orbiting spacecraft in the presence of partial loss of actuator effectiveness, external disturbance and actuator control input saturation problem. In this approach, observer is employed to estimate the value of actuator fault, and a Backstepping attitude controller is then designed to achieve fault tolerant control and external disturbance rejection. The Lyapunov stability analysis shows that the closed-loop attitude system is guaranteed to be almost asymptotically stable. The simulation results show the effectiveness of the derived control law.