基于数字仿真的再入飞行器滚转异常边界条件研究

提出了一种基于数字仿真的再入弹头滚转异常边界条件的确定方法。即：首先给出可精确描述考虑各种气动力（矩）系数、各种干扰源作用时的六自由度运动方程。针对各种干扰源及其组合作用，对某弹头的滚转异常现象作了大量的数字仿真。文中采用一种拟合方法，妥善处理了这些仿真结果，拟合出该弹头滚转异常边界条件的近似解析式     

用人工智能搜索策略进行抗疲劳优化设计

 将人工智能搜索策略应用于抗疲劳优化设计中,针对工程实际中大量存在的离散变量的优化问题,提出了一套不同于传统数学规划法的方法,从根本上解决了处理离散变量的困难。还以多钉多层板接头为算例,作了优化计算,说明本文提出的方法可行,计算程序适用。并且优化结果比数学规划法好。     

基于改进人工蜂群算法的多值属性系统故障诊断策略

针对实际工程应用中常见的多值属性系统故障诊断策略问题,在传统人工蜂群算法(Artificial Bee ColonyAlgorithm,简称 ABC算法)的基础上,提出改进蜂群算法用于多值属性系统的测试序列寻优。首先,在蜂群算法中重新定义多值 D矩阵和五元组的含义;其次,引入方向信息概率矩阵,设置状态转移规则和矩阵元素更新策略;最后,采用导弹舵系统实例说明算法的实现过程和有效性。最终测试序列寻优结果表明:与传统的多值 Rollout算法相比,文中所提算法能得到较好的诊断策略结果,具有一定的应用价值。     

Distributed online mission planning for multi-player space pursuit and evasion

There are three important roles in evasion conflict: pursuer, target and defender. Pur-suers’ mission is to access targets;targets’ mission is to escape from pursuers’ capture;defenders’ mission is to intercept pursuers who are potentially dangerous to targets. In this paper, a distributed online mission plan (DOMP) algorithm for pursuers is proposed based on fuzzy evaluation and Nash equilibrium. First, an integrated effectiveness evaluation model is given. Then, the details of collaborative mission planning which includes the co-optimization of task distributing, trajectory and corresponding maneuvering scheme are presented. Finally, the convergence and steadiness of DOMP are discussed with simulation results. Compared with centralized mission planning, DOMP is more robust and can greatly improve the effectiveness of pursuing. It can be applied to dynamic scenario due to its distributed architecture.     

航空公司航线重组探讨

三大航空集团成立后，合理地调整航线成为企业再生产的基础。航线资源的重组要符合航空公司经营策略，即低成本策略、差异策略还是集中一点策略。在分析经营战略特点的基础上．研究了航线重组的策略。每种策略都要本着提高航线网络的质量和航班效率的原则。     

An object-level strategy for pan-sharpening quality assessment of high-resolution satellite imagery

Current satellite imaging systems offer a trade-off between high spatial and high spectral resolution providing panchromatic images at a higher spatial resolution and multispectral images at a lower spatial resolution but rich in spectral information while a wide range of applications need the highest level of this information, simultaneously. Image fusion techniques as means of enhancing the information content of initial panchromatic and multispectral images produce new images, titled pan-sharpened, which inherent the advantages of the initial images. Considering the impact of fusion accuracy on the quality of corresponding applications, it is necessary to evaluate the quality of these processed images. During the last decade, a lot of quality evaluation metrics have been proposed which are mostly inspired by traditional image quality metrics. These methods are mostly based on applying quality metrics at the pixel level and evaluating final quality value based on averaging of obtained metric values through the whole image. However, obtained results clearly show that the behaviour of image fusion quality is inconsistent amongst different image objects. In this article, by applying image fusion quality metrics (IFQMs) to image objects, an object-level strategy for quality assessment of the image fusion process is proposed. The proposed strategy is applied to different satellite imagery covering residential and agricultural areas. Experimental results show higher capabilities of object-level quality assessment strategy in the quality assessment of the fusion process. Evaluating fusion quality at the object level provides the potential of fusion quality assessment for each individual image object in compliance with different parameters such as the type of objects and the effective size of objects in data set.     

基于VxWorks的空调系统控制软件设计

基于Vx Works软件环境,针对空调系统工作模式多、工作模式之间逻辑复杂等特点开发了空调系统的控制软件。将系统的功能按照任务优先权行划分,并采用状态转换机实现的模式间的转换。通过Tornado软件调试环境,对软件设计进行了修改和完善,保证了空调系统软件的正确性。     

Efficiency optimized fuel supply strategy of aircraft engine based on air-fuel ratio control

Accurate fuel injection control of aircraft engine can optimize the energy efficiency of UAV power system while meeting the propeller speed requirement. Traditional injection control method such as open-loop calibration causes instability of fuel supply which brings the risk of power loss of UAV. Considering that the closed-loop control of AFR can ensure a stable fuel feeding, this paper proposes an AFR control based fuel supply strategy in order to improve the efficiency of fuel-powered UAV while obtaining the required engine speed. According to the optimum fuel injection results, we implement fuzzy-PID method to control the set AFR in different situations. Through simulation and experiment studies, the results indicate that, to begin with, the calibrated mathematical model of the aircraft engine is effective. Next, this fuel supply strategy based on AFR control can normally realize the engine speed regulation, and the applied control algorithm can eliminate the overshoot of AFR throughout all the working progress. What is more,the fuel supply strategy can averagely shorten the response time of the engine speed by about two seconds. In addition, compared with the open-loop calibration, in this work the power efficiency is improved by 9% to 33%. Last but not the least, the endurance can be improved by 30 min with a normal engine speed. This paper can be a reference for the optimization of UAV aircraft engine.     

A heuristic cabin-type component alignment method based on multi-source data fusion

In cabin-type component alignment, digital measurement technology is usually adopted to provide guidance for assembly. Depending on the system of measurement, the alignment process can be divided into measurement-assisted assembly (MAA) and force-driven assembly. In MAA, relative pose between components is directly measured to guide assembly, while in force-driven assembly, only contact state can be recognized according to measured six-dimensional force and torque (6D F/T) and the process is completed based on preset assembly strategy. Aiming to improve the efficiency of force-driven cabin-type component alignment, this paper proposed a heuristic alignment method based on multi-source data fusion. In this method, measured 6D F/T, pose data and geometric information of components are fused to calculate the relative pose between components and guide the movement of pose adjustment platform. Among these data types, pose data and measured 6D F/T are combined as data set. To collect the data sets needed for data fusion, dynamic gravity compensation method and hybrid motion control method are designed. Then the relative pose calculation method is elaborated, which transforms collected data sets into discrete geometric elements and calculates the relative poses based on the geometric information of components. Finally, experiments are conducted in simulation environment and the results show that the proposed alignment method is feasible and effective.     

Multi-UAV coordination control by chaotic grey wolf optimization based distributed MPC with event-triggered strategy

The paper proposes a new swarm intelligence-based distributed Model Predictive Control (MPC) approach for coordination control of multiple Unmanned Aerial Vehicles (UAVs). First, a distributed MPC framework is designed and each member only shares the information with neighbors. The Chaotic Grey Wolf Optimization (CGWO) method is developed on the basis of chaotic initialization and chaotic search to solve the local Finite Horizon Optimal Control Problem (FHOCP). Then, the distributed cost function is designed and integrated into each FHOCP to achieve multi-UAV formation control and trajectory tracking with no-fly zone constraint. Further, an event-triggered strategy is proposed to reduce the computational burden for the distributed MPC approach, which considers the predicted state errors and the convergence of cost function. Simulation results show that the CGWO-based distributed MPC approach is more computationally efficient to achieve multi-UAV coordination control than traditional method.