Online scheduling of distributed Earth observation satellite system under rigid communication constraints

This paper focused on online scheduling of distributed Earth observation satellite system in a dynamic environment. The objective was to maximize the total profit of the overall system by efficiently coordinating the different satellites with stochastic arrival of urgent tasks, subject to rigid communication and observation time window constraints. We formulated this problem as a single-task, single-robot, time-extended assignment problem with intra-schedule dependency using the multi-robot task assignment taxonomy and formulated the sub-problem after releasing urgent tasks in a mixed-integer linear programming model. We first described the online scheduling algorithm for a single satellite, then we proposed the modified consensus-based bundle algorithm (m-CBBA) and modified asynchronous consensus-based bundle algorithm (m-ACBBA) with synchronous and asynchronous communication, respectively. Compared with initial versions of CBBA and ACBBA, the modified versions added the communication loop prediction phases to efficiently utilize scarce communication opportunities and reduce the communication requirements. Additionally, we introduce two contract net protocol (CNP)-based algorithms for comparison, respectively SingleItem-CNP-based (SI-CNP) algorithm and Batch-CNP-based (BA-CNP) algorithm. Computational experiments indicated that both the total profit and percentage of scheduled urgent tasks achieved by the m-ACBBA and m-CBBA algorithms were much higher than those achieved by both SI-CNP and BA-CNP. Additionally, the number of communications needed by either m-ACBBA or m-CBBA algorithm was lower than that by SI-CNP. When the communication cost in the system is high, the m-CBBA algorithm is preferred because it balances the profit and the required number of communications. When the communication cost is low, the m-ACBBA algorithm is preferred because it achieves high total profit and high percentage of scheduled urgent tasks.     

Hybrid integration method for highly maneuvering radar target detection based on a Markov motion model

To detect highly maneuvering radar targets in low signal-to-noise ratio conditions, a hybrid long-time integration method is proposed, which combines Radon-Fourier Transform (RFT), Dynamic Programming (DP), and Binary Integration (BI), named RFT-DP-BI. A Markov model with unified range-velocity quantification is formulated to describe the maneuvering target’s motion. Based on this model, long-time hybrid integration is performed. Firstly, the whole integration time is divided into multiple time segments and coherent integration is performed in each segment via RFT. Secondly, non-coherent integration is performed in all segments via DP. Thirdly, 2/4 binary integration is performed to further improve the detection performance. Finally, the detection results are exported together with target range and velocity trajectories. The proposed method can perform the long-time integration of highly maneuvering targets with arbitrary forms of motion. Additionally, it has a low computational cost that is linear to the integration time. Both simulated and real radar data demonstrate that it offers good detection and estimation performances.     

基于直升机/发动机非线性综合仿真模型的ALQR控制器设计

构建了UH-60A直升机六自由度非定常、非线性气动力模型以及完整的直升机/涡轴发动机非线性综合仿真模型。使用增广LQR方法设计了直升机飞行控制器,包线内大量仿真结果及与 控制器效果的对比表明该控制器解耦性能、指令跟踪性能优越,鲁棒性强。此外,该控制器设计过程简单和调参方便。借助上述综合仿真模型研究了发动机闭环系统与直升机的功率匹配关系,数字仿真表明,发动机能够满足直升机机常规飞行任务下的功率需求,功率涡轮转速下垂量满足直升机飞行操纵品质规范（ADS-33E）的要求。     

基于Markov理论的反舰导弹突防舰载防空火炮效能评估

采用Markov理论,考虑海浪对防空火炮射击精度的影响,建立反舰导弹突防舰载防空火炮效能评估模型,动态地评估m枚反舰导弹随距离、海况等级变化突防n座防空火炮的突防率,确定要击毁军舰需要突防防空火炮的反舰导弹的枚数。     

部分可观测信息条件下装备剩余寿命预测

 针对部分可观测信息条件下退化系统的剩余寿命(RUL)预测问题,综合利用装备的历史寿命信息和性能退化信息,采用隐马尔可夫模型(HMM)对系统进行状态评估,得到系统的转移概率矩阵和观测概率矩阵;采用Bayes方法不断更新系统状态空间的条件概率分布;利用比例故障率模型(PHM)对系统进行可靠性分析,得到系统的故障率和可靠度函数,进而得到装备的剩余寿命分布。研究表明,该方法可较准确地预测装备的剩余寿命,为保障人员提供科学的维修决策依据。     

基于Markov模型的机群完好率研究

通过建立非线性模型对机群的完好率进行研究。针对完好飞机,重点研究飞行批次对完好率的影响;对于故障飞机,重点研究中修级维修和串件维修对修复率的影响,进而得出在基层级维修能力下机群满足总体完好率要求的持续时间。     

采用内积原理建立航空发动机神经网络辨识模型

根据样本空间的内积特性,提出一种无需迭代学习内积神经网络。以某型航空发动机的机载记录数据为例,对发动机进行了建模,结果表明该方法具有自学习速度快、抗干扰能力强、准确性高的特点。     

高硅氧增强塑料烧蚀模型中热解层厚度的探讨

通过小型实验固体火箭发动机的多次热试车,对喷管扩散段截面上高硅氧酚醛材料的色变厚度进行了观察,对该截面上材料采用红外光谱成份分析和导电性测量,确认了热解层厚度与碳化层厚度具有相同的数量级,可达2.5mm左右.因此,在作高硅氧酚醛喷管材料的烧蚀与温度场计算时,不宜采用热解面模型,而应采用热解层模型.     

燃气轮机转子动力特性分析的旋转对称有限元模型

本文给出了燃气轮机转子临界转速和不平衡响应计算分析的旋转对称有限元模型,付立叶级数的引入可以使得三维转子只在一个基础扇区上使用三维单元建立有限元模型。与梁单元相比,实体单元能准确描述转子的几何形状。文中给出了一个验证性算例和一个工程实例。      

脉冲爆震发动机的飞行性能计算与分析

为了获得脉冲爆震发动机的飞行性能参数随飞行高度和飞行速度的变化规律,在应用最小G ibbs自由能理论建立求解爆震燃烧的平衡成分及其浓度、平衡参数的基本关系式,据此对爆震波特性参数进行数值模拟的基础上,通过引入进气道和尾喷管建立了一定飞行状态下的多管自吸气式脉冲爆震发动机理论性能计算模型,对脉冲爆震发动机的性能随飞行高度、速度的变化趋势进行研究。结果表明,在不同飞行高度和飞行马赫数的状态下,脉冲爆震发动机性能有一定的变化规律,同时模型也考虑了加入尾喷管对性能的影响,为脉冲爆震发动机的性能分析与理论设计提供了依据。