Predictive fault-tolerant control of an all-thruster satellite in 6-DOF motion via neural network model updating

The problem of controlling an all-thruster spacecraft in the coupled translational-rotational motion in presence of actuators fault and/or failure is investigated in this paper. The nonlinear model predictive control approach is used because of its ability to predict the future behavior of the system. The fault/failure of the thrusters changes the mapping between the commanded forces to the thrusters and actual force/torque generated by the thruster system. Thus, the basic six degree-of-freedom kinetic equations are separated from this mapping and a set of neural networks are trained off-line to learn the kinetic equations. Then, two neural networks are attached to these trained networks in order to learn the thruster commands to force/torque mappings on-line. Different off-nominal conditions are modeled so that neural networks can detect any failure and fault, including scale factor and misalignment of thrusters. A simple model of the spacecraft relative motion is used in MPC to decrease the computational burden. However, a precise model by the means of orbit propagation including different types of perturbation is utilized to evaluate the usefulness of the proposed approach in actual conditions. The numerical simulation shows that this method can successfully control the all-thruster spacecraft with ON-OFF thrusters in different combinations of thruster fault and/or failure.     

Assessment on critical technologies for conceptual design of blended-wing-body civil aircraft

Civil aviation faces great challenges because of its robust projected future growth and potential adverse environmental effects. The classical Tube-And-Wing(TAW) configuration following the Cayley's design principles has been optimized to the architecture's limit, which can hardly satisfy the further requirements on green aviation. By past decades' investigations the BlendedWing-Body(BWB) concept has emerged as a potential solution, which can simultaneously fulfill metrics of noise, emission and fuel burn. The purpose of the present work is to analyze the developments of critical technologies for BWB conceptual design from a historical perspective of technology progress. It was found that the high aerodynamic efficiency of BWB aircraft can be well scaled by the mean aerodynamic chord and wetted aspect ratio, and should be realized with the trade-offs among stability and control and low-speed performance. The structure concepts of non-cylinder pressurized cabin are of high risks on weight prediction and weight penalty. A static stability criterion is recommended and further clear and adequate criteria are required by the evaluations of flying and handling qualities. The difficulties of propulsion and airframe integration are analyzed. The energy to revenue work ratios of well-developed BWB configurations are compared,which are 31.5% and 40% better than that of TAW, using state-of-art engine technology and future engine technology, respectively. Finally, further study aspects are advocated.     

Contingency target assessment,trajectory design,and analysis for NASA’s NEA scout solar sail mission

The presented study examines contingency target selection and trajectory design for NASA’s Near-Earth Asteroid Scout mission under the assumption of a missed lunar gravity assist. Two previously considered asteroids are selected as potential targets for the given scenario based on favorable orbital characteristics for launch dates ranging from June 27, 2020 through July 26, 2020. Initially, a simplified circular restricted 3-body problem + ideal solar sail model is utilized to survey trajectory options for a month-long launch window. Selected solutions from this data set are then converged in an N-body ephemeris + non-ideal sail model. Results suggest that NEA Scout can still perform asteroid rendezvous mission under the missed lunar gravity assist scenario with new targets, 2019 GF1, 2018 PK21, and 2007 UN12, based on the target launch dates. Further target assessment is carried out for 165 days beyond the current June 27, 2020 launch date.     

Application of a PCA-DBN-based surrogate model to robust aerodynamic design optimization

An efficient method employing a Principal Component Analysis (PCA)-Deep Belief Network (DBN)-based surrogate model is developed for robust aerodynamic design optimization in this study. In order to reduce the number of design variables for aerodynamic optimizations, the PCA technique is implemented to the geometric parameters obtained by parameterization method. For the purpose of predicting aerodynamic parameters, the DBN model is established with the reduced design variables as input and the aerodynamic parameters as output, and it is trained using the k-step contrastive divergence algorithm. The established PCA-DBN-based surrogate model is validated through predicting lift-to-drag ratios of a set of airfoils, and the results indicate that the PCA-DBN-based surrogate model is reliable and obtains more accurate predictions than three other surrogate models. Then the efficient optimization method is established by embedding the PCA-DBN-based surrogate model into an improved Particle Swarm Optimization (PSO) framework, and applied to the robust aerodynamic design optimizations of Natural Laminar Flow (NLF) airfoil and transonic wing. The optimization results indicate that the PCA-DBN-based surrogate model works very well as a prediction model in the robust optimization processes of both NLF airfoil and transonic wing. By employing the PCA-DBN-based surrogate model, the developed efficient method improves the optimization efficiency obviously.     

基于新陈代谢GM（1,1）模型的导弹遥测故障预测算法

在人工监视遥测关键参数是否超出阈值范围以判断导弹故障的传统模式基础上,对GM（1,1）预测模型进行了改进,研究了基于新陈代谢的GM（1,1）预测算法对遥测参数实时预测效果.该算法能不断去掉最老的信息,充分利用最新的信息,避免了预测模型老化的现象;由于用于预测的数列维度较少,便于计算,能够保证算法的实时性.用MATLAB编程实现算法,比对实测数据的预测值与实际值,并进行误差分析.结果表明,该算法对遥测参数的预测精度较高,可为及时发现导弹故障提供科学的依据.     

基于多可信度代理模型的尾喷管优化设计

尾喷管是飞行器机体/推进一体化设计中的关键部件之一,直接影响着飞行器的推阻匹配、俯仰力矩配平等特性。为了提高尾喷管优化设计效率,建立基于多可信度代理模型的多目标优化模型。以基于粗网格、无黏模型的CFD 结果作为低可信度数据,以基于细密网格、SST k-ω 湍流模型的CFD 结果作为高可信度数据,将最大化推力系数、升力系数和俯仰力矩系数作为优化目标,构建Cokriging 模型,并结合NSGA-Ⅱ算法得到Pareto 解集。结果表明：以上三个目标分别提升了2.94%、13.0% 和40.6%,误差低于0.5%,并进行了敏感性分析;优化后流场波系结构更为复杂,改变了壁面压强分布规律;与Kriging 模型相比,Cokriging 模型具有相当的预测性能,构建时间成本节省了62%。     

Double-decoupled inverse design of natural laminar flow nacelle under transonic conditions

The inverse design based on the pressure distribution is an essential approach to realize the improvement of Natural Laminar Flow(NLF) performance for nacelles. However, the direct definition of target pressure distribution at design point is challenging for the dilemma to consider the constraints of shock wave and laminar flow at the same time. In addition, the universality of method will be limited when the inverse design is strongly coupled with the solver. Thus, a double-decoupled methodolog...     

超声速低声爆布局分层优化方法

声爆抑制是发展新一代超声速民机必须突破的关键技术。总体布局参数的合理设计可以使飞行器具有良好的声爆特性。为了提高全局进化算法在布局设计中的优化效率,提出一种基于数据挖掘的分层优化方法,利用数据挖掘中的决策树算法提取设计知识,获得设计变量分层信息,指导低声爆布局分层优化;针对某超声速低声爆飞行器,选取后掠角、上反角、展弦比、梢根比、长细比五个总体布局参数作为设计变量,开展分层优化数值实验,并与一体化优化形成对比验证。结果表明：分层优化方法能够搜索到与一体化优化高度吻合的最优解,分层优化的收敛速度显著高于一体化优化,且对随机寻优历程的表现更稳健。     

航空发动机低压转子系统的“可容模态”设计及实验验证

建立了带弹性支承和阻尼器的航空发动机低压柔性转子动力学模型,进行了模态计算以及临界转速处的响应计算。在考虑临界转速约束与“临界跟随”现象约束的条件下,综合模态不平衡影响因子、弹支应变能占比以及套齿连接结构稳定性构造了可容度评价函数,建立了低压转子系统的“可容模态”优化设计方法。设计并搭建了低压转子实验系统,从模态测试实验、阻尼器减振实验以及长时间“共振”实验,验证了设计方法的可靠性。研究结果为计算的临界转速与实际测量的临界转速最大误差为3.86%,阻尼器在1阶与2阶临界转速处的减振比最大可达45.6%,实验转子系统在1阶与2阶临界转速处各完成了长达412.5 s和429.8 s的“共振”实验,共振过程中转子系统各通道振动单峰值稳定在100μm以内,且无次谐波产生。表明了所建立的航空发动机低压转子系统“可容模态”优化设计方法是可行的。     

航空发动机设计中采用CAD技术的研究

为了进一步加强ＣＡＤ（ＣｏｍｐｕｔｅｒＡｉｄｅｄＤｅｓｉｇｎ）技术在航空发动机设计领域的应用,主要介绍ＡｕｔｏＣＡＤ图形软件的辅助绘图、三维建模的功能及在航空发动机领域的一些应用。目的是在航空发动机设计领域推广及运用ＣＡＤ技术改善发动机的设计方法。