Disturbance observer based model predictive control for accurate atmospheric entry of spacecraft

Facing the complex aerodynamic environment of Mars atmosphere, a composite atmospheric entry trajectory tracking strategy is investigated in this paper. External disturbances, initial states uncertainties and aerodynamic parameters uncertainties are the main problems. The composite strategy is designed to solve these problems and improve the accuracy of Mars atmospheric entry. This strategy includes a model predictive control for optimized trajectory tracking performance, as well as a disturbance observer based feedforward compensation for external disturbances and uncertainties attenuation. 500-run Monte Carlo simulations show that the proposed composite control scheme achieves more precise Mars atmospheric entry (3.8?km parachute deployment point distribution error) than the baseline control scheme (8.4?km) and integral control scheme (5.8?km).     

综合集成系统中基于Agent的模型设计与管理

简要介绍了Agent技术,提出了Agent Model结构和模型综合集成空间(Mspace)概念.在综合模拟系统中,建立了消息队列(MSMQ())模型,以实现对模型的管理与调度.阐述了基于Agent Model结构和模型综合集成空间(Mspace)技术探讨作战仿真类模型,以及实现了模型在交互联合作战仿真集成方面所作的研究.     

基于特征映射的涡轮导向叶片精铸模型自动转换研究

通过对涡轮导向叶片及其精铸模型结构特点的分析,以特征映射理论为依据,提取其结构特征、特征内部的约束关系和构成特征的几何元素,将叶片的内外零件模型添加加工余量、工艺附件、收缩率后得到精铸模具设计和制造所需要的模具型腔体模型,从而完成了精铸模具设计各模型间的自动转换,大大缩短了精铸模具的设计周期,具有重要的理论和实践应用价值.     

简单二体引力模型用于空间目标轨道面交线确定的效果分析

在空间目标碰撞预警分析中，准确地计算出空间目标的轨道面交线是进行地心距筛选、时间差筛选的前提，目前较多使用的快速确定轨道面交线的方法为简单二体引力模型。深入分析该模型，比较了其计算的空间目标轨道面交线与STK计算结果的差异，指出了简单二体引力模型在计算空间目标轨道面交线时的局限性，认为轨道摄动是影响轨道面交线计算准确性的主要原因，应该采用更能反映空间目标实际运动规律的改进的二体引力模型的方法。     

如何建立实际问题的数学模型

通过对一例实际问题的物理分析，结合高等数学知识，阐述建立相应数学模型的方法。     

高阶对象的二阶模型匹配

本文证明了对于一类高阶对象，其输出可以用一系列系数连续变化的线性定常二阶系统的输出组合完全代替。     

浅谈Java 2D图象处理技术

本文介绍了Java 2D API的图象处理思想.通过以LookupOp查找表过滤器为例,分析了图象的即时模式模型,即对内存的缓冲区图象进行处理,再绘制到屏幕上的处理技术.同时介绍了利用Java 2D中提供的过滤器对图象数据的过滤操作.     

北京航天指控中心卫星任务数字仿真软件的设计

首先给出了北京航天指控中心仿真软件的设计模型,阐述了仿真软件仿真的内容,并详细介绍了仿真软件的总体结构和关键进程的设计方法,最后显示了仿真的结果,在实际应用中该软件得到了验证。     

2021 Turkey mega forest Fires: Biodiversity measurements of the IUCN Red List wildlife mammals in Sentinel-2 based burned areas

Mega wildfires are one of the environmental disasters worldwide. This study evaluates the pre-fire species diversity and the indirect effects, including habitat loss for one of the largest wildfires in Manavgat (Antalya-Turkey) in 2021, with a two-step methodology. Here, (1) burnt areas in the Manavgat district (2021) were detected with remote sensing data from Sentinel-2A by delta Normalized Burn Ratio calculation for a selected area in Google Earth Engine, and (2) mammals' habitat vector data of International Union for Conservation of Nature (IUCN) Red List were integrated into Habitat and Biodiversity modelling of Terrset to analyze the alpha, beta, gamma diversity and Range Restriction Index for the wildfire region. In the total 4210 km² study area, 696 km² of the area was damaged by different fire severity; also, there were 56 mammal species' habitats here. These species include bats (i.e. Nyctalus leisleri), felids (i.e. Felis chaus), rodents (i.e. Rattus norvegicus) and large mammals (i.e. Ursus arctos). 88 % of these species are in IUCN's Least Concern category. The remaining classes are Near Threatened (3.7 %) and Vulnerable (7.4 %). This study also indicated that the burnt area's species richness does not totally consist of endemic species. Therefore, pre-fire species richness analyses of this study can be a base for further studies about the species' post-fire activity and occupancy.Furthermore, the 2021 mega wildfires show us the necessity of wildfire monitoring and risk studies in the entire Mediterranean ecosystem to evaluate the risks to the Sustainable Development Goals. Therefore, post-fire spatial data, fire migration monitorization, and recording of the species' activities should be performed temporally. In this way, the ability of wildlife's recovering, and the direct and indirect effects of the fire will be examined for ecosystems in the long term.     

A new modeling scheme for powered parafoil unmanned aerial vehicle platforms: Theory and experiments

A novel framework is established for accurate modeling of Powered Parafoil Unmanned Aerial Vehicle (PPUAV). The model is developed in the following three steps: obtaining a linear dynamic model, simplifying the model structure, and estimating the model mismatch due to model variance and external disturbance factors. First, a six degree-of-freedom linear model, or the structured model, is obtained through dynamic establishment and linearization. Second, the data correlation analysis is adopted to determine the criterion for proper model complexity and to simplify the structured model. Next, an active model is established, combining the simplified model with the model mismatch estimator. An adapted Kalman filter is utilized for the real-time estimation of states and model mismatch. We finally derive a linear system model while taking into account of model variance and external disturbance. Actual flight tests verify the effectiveness of our active model in different flight scenarios.