多目标优化方法库的开发与应用

多目标优化方法库是一个专门针对多目标问题的优化软件。本文介绍了用面向对象方法对方法库进行开发的过程,着重说明了该软件以优化模型为中心的主体框架和以优化算法为核心的模块化结构,以及库中采用的各种多目标优化算法特别是非劣分层遗传算法。最后通过算例说明了方法库的使用方法,证明了其良好的操作性和库中算法优良的性能。     

Hybrid partition- and network-level scheduling design for distributed integrated modular avionics systems

Distributed Integrated Modular Avionics (DIMA) develops from Integrated Modular Avionics (IMA) and realizes distributed integration of multiple sub-function areas. Time-triggered network provides effective support for time synchronization and information coordination in DIMA systems. However, inconsistency between processing resources and communication network destroys the time determinism benefiting from partitions and time-triggered mechanism. To ensure such time determinism and achieve guaranteed real-time performance, system design should collectively provide a global communication scheme for messages in network domain and a corresponding execution scheme for partitions in processing domain. This paper firstly establishes a general DIMA model which coordinates partitioned processing and time-triggered communication, and then proposes a hybrid scheduling algorithm using Mixed Integer Programming to produce feasible system schemes. Furthermore, incrementally integrating new functions causes upgrades or reconfigurations of DIMA systems and will generate integration cost. To control such cost, this paper further develops an optimization algorithm based on Maximum Satisfiability Problem and guarantees that the scheduling design for upgraded DIMA systems inherit their original schemes as much as possible. Finally, two typical cases, including a simple fully connected DIMA system case and an industrial DIMA system case, are constructed to illustrate our DIMA model and validate the effectiveness of our hybrid scheduling algorithms.     

Intelligent modeling and identification of aircraft nonlinear flight

In this paper, a new approach has been proposed to identify and model the dynamics of a highly maneuverable fighter aircraft through artificial neural networks（ANNs）. In general, aircraft flight dynamics is considered as a nonlinear and coupled system whose modeling through ANNs, unlike classical approaches, does not require any aerodynamic or propulsion information and a few flight test data seem sufficient. In this study, for identification and modeling of the aircraft dynamics, two known structures of internal and external recurrent neural networks（RNNs） and a proposed structure called hybrid combined recurrent neural network have been used and compared.In order to improve the training process, an appropriate evolutionary method has been applied to simultaneously train and optimize the parameters of ANNs. In this research, it has been shown that six ANNs each with three inputs and one output, trained by flight test data, can model the dynamic behavior of the highly maneuverable aircraft with acceptable accuracy and without any priori knowledge about the system.     

时变线性系统的全程滑态变结构控制研究

本文采用分段定常的处理方法研究了一般时变线性系统的滑态变结构控制方案，提出了实时自动分段原则与相应的全程滑态结构控制算法，并通过数字仿真验证了该方案的有效性。     

民用飞机气动力模型建模方法研究

对民机常用的两种气动力建模方法——全机建模法和分部件组合建模法进行了研究,并对两者的优缺点进行了对比分析,进而对两类方法在大型客机气动力建模中的综合运用提出了建议。     

基于遗传算法的柴油机喷油系统模型参数辨识

柴油机喷油系统中压力的变化会引起气泡的产生和溃灭,而气泡的变化会对燃油的流动和压力波的传播产生影响.为了更准确预测喷油系统中的初始含气率以及变化情况,提出了应用改进遗传算法对柴油机喷油系统模型中的柱塞腔、出油阀紧帽腔、高压油管和针阀腔初始含气率进行辨识的新方法.基于气泡模型,建立了气-液两相条件下的柴油机喷油系统模型,通过仿真数据和试验数据对比,构造了适应度函数,实现了对柴油机喷油系统模型的参数辨识,并得到了参数优化后的柴油机喷油系统模型.仿真结果与试验数据的比较验证了采用改进遗传算法对气-液两相条件下的柴油机喷油系统模型进行参数辨识的可行性.     

空间延迟/中断容忍网络路由算法性能评估

文章主要针对空间延迟/中断容忍网络（Delay/disruptionTolerantNetworks,DTNF）路由算法的性能进行分析评估,为未来空间DTN路由技术的设计提供参考和建议。首先,从利用网络知识多少的角度,对目前提出的适用于空间DTN的路由算法进行了分析和比较;然后,在一个典型空间DTN场景下,通过设定不同的接触计划,从微观和宏观两个方面,对最早投递(EarliestDelivery,ED)、基于本地队列的最早投递(EarliestDeliverywithLocalQueue,EDLQ)、接触图路由(ContactGraphRouting,CGR)、和基于最早传输机会的接触图路由(ContactGraphRoutingEarliestTransmissionOpportunity,CGR ETO)几种典型空间DTN路由算法的性能进行了仿真评估;最后,对仿真评估结果进行了分析和总结,并对未来空间DTN路由算法的研究提出了建议。仿真结果表明,对于端到端延时和束投递完成率两项性能指标,ED性能最差,CGR次之,EDLQ和CGR ETO的性能相当。     

多星任务规划中的FFFS-DTMB与ADTPC-DTMB算法

 多星对地观测任务规划是一类典型组合优化问题,针对该问题中常见的时间窗口冲突问题,根据同一时间窗口内的冲突任务的处理方式提出了两种有效处理此类问题的规划算法：带有冲突任务时间窗口后移的先完成先规划算法(FFFS DTMB)以及冲突任务共存性判断算法(ADTPC DTMB),并给出了关键步骤的算法过程与伪代码。完整的卫星任务规划过程包括了约束检查、优先级检查以及任务规划,不考虑任务间关系与优先级,主要研究处理具有时间窗口冲突的任务规划算法。文中给出的两种算法优化目标均为最大化规划任务数量。算法的主要思路是通过采用一个冲突任务替换一个已规划的任务,并将替换任务后移至下一时间窗口或在同一时间窗口内部后移。最终的评价结果显示了两种算法的有效性。     

一种基于偏好MOEA的卫星地面站资源多目标优化算法

随着中国航天事业的发展,卫星地面站资源匮乏问题日益突出,需要对其进行统筹优化使用。因此,卫星地面站资源规划问题得到了广泛关注。在分析问题特点的基础上,对用户规划结果的偏好信息进行建模表达,建立了涵盖用户偏好的多目标数学规划模型,提出了基于偏好多目标进化算法的卫星地面站资源规划算法。为了进一步提升算法性能,设计了基于领域知识的启发式策略,包括：任务扩充策略、冲突消解策略以及任务缩减策略等。实验结果表明,与现有算法相比,用户偏好信息的引入能有效提升问题求解针对性,在IGD-CF （Inverted Generational Distance based on Composite Front）指标上取得了更好的效果。     

低空目标电波折射修正中地球半径计算方法

在防御体系中雷达对低空目标一般呈俯视状况,因此在电波折射修正中必须把地球视为椭球,而不能视为圆球体,否则会产生很大误差.本文通过雷达测量参数和大地坐标与空间坐标的转换,给出了计算雷达电波射线上任意一点对应地球半径的方法.