关于中国航空企业实施先进制造模式的思考

从先进制造模式的涵义和特点入手 ,阐述了先进制造模式在国外航空企业的应用状况 ,分析了先进制造模式在中国航空企业中实施的可行性和途径。     

飞机穿越烟气流场的响应计算与分析

本文把烟气流作为一种人为的风切变场,分析和计算了烟气流的抬升夹卷模式,讨论了飞机对称穿越烟气流场时的响应。可为电厂和机场的相关设计提供参考依据。     

飞机带外挂对称结构振型局部化的参数影响

本文在文〔１〕研究的基础上，详细分析了飞机左右对称子结构间的耦合度以及外挂联接刚度失调量的大小等因素对振型局部化程度的影响。通过具体的数据揭示了各参数对局部化程序的影响规律。     

卫星用半导体器件失效模式和机理分布

以中国空间技术研究院电子元器件可靠性中心1987～1990四个年度数百份失效分析报告为依据,得到卫星用半导体器件解剖前失效模式分布:逻辑失控占36.3%,开路占22.2%等;失效机理分布:铝腐蚀占1 6.3%,使用不当占14.6%等。该项研究以第一手数据首次全面、系统指出卫星用器件失效模式和机理。为卫星可靠性设计、优选器件厂及器件厂采取措施提供重要依据。     

快速阀门同步控制系统

本文阐述了自在由飞弹道靶试验中,利用微波相干原理,取得模型运动的起步信号,经过与模型运动速度相对应的延时后,去触发控制电路,引爆阀体内的电雷管,控制阀门的开启和关闭的同步控制系统。     

纳米碳粉掺杂对激光烧蚀GAP的推进性能影响

实验以含能聚合物聚叠氮缩水甘油醚(Glycidyl azide polymer,GAP）作为激光烧蚀微推力器的靶材。通过对不同浓度纳米碳粉掺杂和靶材厚度下激光烧蚀GAP的比冲、冲量耦合系数和能量转化效率测量，结合靶材喷射羽流图像，分析了纳米碳粉掺杂提高激光烧蚀聚合物靶材推进性能的机理，给出纳米碳粉掺杂的适用方式。实验结果表明：透射式下，掺杂纳米碳粉之后，聚合物对激光的吸收大幅增强，但激光烧蚀推进性能不随掺杂浓度增加而显著提升；纳米碳粉吸收激光能量形成温度极高的局部热区促进聚合物中化学能的释放，是推进性能提升的主要原因；掺杂纳米碳粉之后的GAP烧蚀深度降低，表现出面吸收特性；随着靶材厚度的增加，未完全烧蚀的工质质量增加，使得靶材的利用率大大降低，导致聚合物推进性能下降。实验中掺杂3%纳米碳粉、厚度为54 μm的GAP靶材最优能量转化效率超过250%，适合作为透射式激光烧蚀微推力器的靶材。     

Maximal admissible mode decision delay in terminal guidance

Mode decision-maker is a critical component in the logic-based Integrated Estimation and Guidance(IEG) system. For the best possible estimation and guidance performance, the mode decision delay of the mode decision-maker should be limited to a range as small as possible. This paper presents a numerical method for computing the maximal admissible mode decision delay that varies with time-to-go. Particular attention has been paid to highly maneuvering target interception in terminal guidance. The results of this research offer useful guidelines for the design of the mode decision-maker in IEG systems.     

考虑输入饱和的固定翼无人机自适应增益滑模控制

针对复杂环境下的固定翼无人机飞行控制问题，考虑输入饱和以及复杂外界干扰的影响，提出一种基于自适应滑模控制方法的固定翼无人机飞行控制策略。首先，对固定翼无人机模型进行介绍，将模型分为姿态子系统和速度子系统；其次，针对姿态子系统和速度子系统的特点以及控制需求，分别采用自适应多变量螺旋滑模和自适应快速超螺旋滑模设计姿态控制器和速度控制器，该策略无需设计干扰观测器对外界干扰进行估计，仍然可以实现固定翼无人机对姿态参考指令和速度参考指令的有限时间精确跟踪，并基于Lyapunov的稳定性分析方法证明了闭环系统的稳定性。最后，对本文所提出的控制策略进行了仿真验证，结果表明该控制策略具有良好的控制性能。     

Backstepping sliding-mode control of stratospheric airships using disturbance-observer

In the presence of unknown disturbances and model parameter uncertainties, this paper develop a nonlinear backstepping sliding-mode controller (BSMC) for trajectory tracking control of a stratospheric airship using a disturbance-observer (DO). Compared with the conventional sliding mode surface (SMS) constructed by a linear combination of the errors, the new SMS manifold is selected as the last back-step error to improve independence of the adjustment of the controller gains. Furthermore, a nonlinear disturbance-observer is designed to process unknown disturbance inputs and improve the BSMC performances. The closed-loop system of trajectory tracking control plant is proved to be globally asymptotically stable by using Lyapunov theory. By comparing with traditional backstepping control and SMC design, the results obtained demonstrate the capacity of the airship to execute a realistic trajectory tracking mission, even in the presence of unknown disturbances, and aerodynamic coefficient uncertainties.     

Two-stream instability generation in the lunar ionosphere

The Two-stream Instability (TSI) generation is studied analytically in the lunar ionosphere. The TSI is a tiny perturbation in the electron plasma density, due to which an electric field grows with time and this growth is facilitated by the electron plasma in the background. In lunar ionosphere, the TSI comes into existence when the solar wind interacts unhindered with the tenuous lunar electron plasma in the surface bound exosphere. In this study, the conditions which allow the TSI to form and the subsequent instability growth with time i.e. the growth factor, is estimated. Initially, the threshold condition for the TSI to take place is determined. Thereafter, the solar wind and lunar plasma parameter contribution to trigger TSI is investigated along with the effect of these parameters in the evolution of TSI. The plasma TSI evolution with the passage of time is also depicted in phase space diagram with Particle-In-Cell simulations.