破产问题的网络对策模型

讨论了合作对策中破产对策与最小费用树对策的各种解之间的关系，通过构造网络图，给出了将破产问题化为最小费用树对策的一个充分条件，从而给出了破产对策核仁解的一种有效方法     

基于Nash均衡与进化计算的协调航迹规划

在对策论框架下研究多无人飞行器的协调航迹规划问题,提出了一种基于Nash平衡和进化计算的航迹规划算法.协调航迹规划是一个多目标合作优化问题,也是一个非合作对策问题.飞行器编队的分布结构提供了一种隐性偏好信息,有助于找到飞行器编队的最优协调航迹和最优飞行代价分配.本文算法使用特定的航迹个体表示方法和进化算子,按照层次方法处理各种航迹约束.不同飞行器间的协同和竞争关系定义在航迹评价函数里.仿真结果验证了基于博弈论航迹规划算法的可行性和优越性.     

单调集对策的核心单调分配法

在分析Young,H.P.Monotonic,H.P.Cost,L.Jew等人对合作对策联盟单调的核心分配法研究的基础上,证明了任意人单调集对策总存在联盟单调的核心分配法.     

飞机地面除冰运行合作博弈模型研究

通过对飞机除冰运行问题的分析研究,以合作博弈的思想为理论基础,建立了在允许合作选择对策并且进行支付转移规则下的航空公司博弈模型,通过对模型核心与特征函数的分析,基于Shapley向量的博弈核心求解方法得以提出。仿真结果表明,该合作博弈模型有效激励了航空公司间的合作行为,基于Shapley向量核心解法兼顾了联盟的集体理性与个体理性,对比显示,其分配方案合理、较优。     

考虑低空运行环境求解无人机任务分配问题的研究

在低空救援中如何合理的分配无人机的搜救任务长期以来都是研究的重点。本文在分层级分布式分配方法的基础上建立多目标多无人机任务分配模型,在模型中以搜救费用、无人机使用数量、完成任务的均衡性为目标函数,并且采用改进的NSGA-Ⅱ算法进行求解。结果表明：本文建立的模型有效,能在不同搜救环境下给出合理有效的分配方案;在搜救中考虑以搜救效率最高为导向时,带来无人机成本和数量的增加;当实际搜救的无人机非常有限时,则需要时间成本的投入;以经济利益为导向时,则会导致搜救时间的增加。     

试论资产评估

在改革开放过程中,经济生活中出现了许多新变化,尤其是产权转让过程中的资产评估是一个迫切需要解决的理论问题与实际问题。本文着重讨论资产评估的五个问题:资产评估的性质与内涵、资产评估的理论基础、资产评估的标准、资产评估的方法以及资产评估机构的设置。     

线性随机系统Kalman滤波的野值修正

本文讨论原始输入采样数据含有野值时Kalman滤波的修正问题,提出了一组易于应用的处理对策与计算方法。     

线性随机系统Kalman滤波的野值修正

本文讨论原始输入采样数据会有野值时Kalman滤波的修正问题，提出了一组易于应用的处理对策与计算方法。     

基于弹簧-悬臂梁模型最小变形能的气动载荷分配方法

在进行气动载荷到结构载荷转换时使用弹簧-悬臂梁模型来代替悬臂梁模型,解决了如果气动载荷点与部分结构节点重合则会导致难以求解的问题,载荷分配结果符合“近大远小”的规律,且分配前后完全符合等效性。研究了模型参数对载荷分配结果的影响,讨论了利用悬臂梁与弹簧刚度比,刚度与目标点距离的比来控制分配结果的方法。另外,讨论了使用构造函数代替物理模型的方法。     

试论企业资产评估的若干理论问题

本文重点论述了“资产评估”的科学内涵、资产价值的绝对性与相对性原理,资产计价基础以及企业资产评估应遵循的一般原则等理论问题,以期作为构想资产评估方法时的参考依据。     

Load distribution strategy for multi-lift system with helicopters based on power consumption and robust adaptive game control

It is of great significance to reasonably distribute the slung load to each helicopter while considering difference in power consumption, relative position and interaction comprehensively. Therefore, the load distribution strategy based on power consumption and robust adaptive game control is proposed in this paper. The study is on a “2-lead” multi-lift system of four tandem helicopters carrying a load cooperatively. First, based on the hierarchical control, the load distribution problem is divided into two parts: the calculation of expected cable force and the calculation of the anti-disturbance cable force. Then, aimed at minimizing the maximum equivalent power of helicopter, an optimization problem is set up to calculate the expected cable force. Specially, the agent power model is trained by BP neural network, the safe distance constraint between helicopters is set to 2.5 rotor diameters to reduce aerodynamic interference, and the helicopters with different performance can be considered by introducing the equivalent power factor into the objective function. Next, considering the difference and interaction between helicopters, the robust adaptive differential game control is proposed to calculate the anti-disturbance cable force. Particularly, to solve the coupled Hamiltonian equations, an adaptive solving method for value function is proposed, and its stability is proved in the sense of Lyapunov. The simulation results indicate that the proposed load distribution method based on power consumption is applicable to the entire flight trajectory even there are differences between helicopters. The game control can consider interaction between helicopters, can deal with different objective functions, and has strong robustness and small steady-state error. Based on the entire strategy, the cable force can be reasonably allocated so as to resist disturbance and improve the flight performance of the whole system.     

空战决策中的智能微分对策法

提出了空战决策中的一种新方法-智能微分对策法。该方法在整体战术制定中采用人工智能方法，在空战的各个子阶段的具体战术决策中采用微分对策方法。提出了智能微分对策点的定义，它在某些情况下利用人工智能预测对手的策略，将微分对策转化为两个独立的单边极值问题，从而拓宽了微分对策在空战中的应用范围，利用智能微分对策法建立了空战决策模型，并进行了空战仿真，仿真结果表明，该方法优于专家系统法。     

大气层内拦截弹微分对策制导律对策空间分布研究

 摘〓要〖HTSS〗: 为提高机动性和操作性,大气层内拦截弹多采用气动力/喷流反作用力（RCS）复合控制系统。在RCS工作时间有限的条件下,建立线性化对策模型,并利用微分对策理论研究了复合控制系统对3种可能对策空间的分布影响。RCS的使用时机不同,其对微分对策空间分布的影响也不同。基于对策空间的分布确定了RCS的使用时机,并给出了适合实际应用的制导策略。仿真研究表明本文提出的应用时机与制导策略能够实现气动力与RCS之间的有机结合,使制导指令达到最优分配,显著地提高了制导精度。     

蜂群对抗决策故障下的容错博弈控制

针对大规模分簇蜂群无人机的任务分配问题,考虑对抗场景下某些无人机由于受到敌方攻击或操控,决策规则遭到篡改,进而导致群决策行为与期望的均衡点产生偏差的决策故障。在演化矩阵博弈的框架下,运用多群体复制子动态方程对蜂群无人机和故障建模,基于李雅普诺夫函数对故障发生前后均衡点的局部渐近稳定性及其吸引域进行了分析,从而建立了自容错条件,并设计了基于激励的簇间协同容错博弈控制方法,对群决策行为偏差进行补偿,使得蜂群任务分配状态在故障下仍能达到期望的均衡点,获得理想的分工收益。     

固定资产价值评估方法的探讨

本文通过了对影响固定资产价值的各种因素的分析，指出了成新率指标是影响固定资产价值的关键因素，探讨了运用模糊教学的二级综合评价法求出成新率，进而确定固定资产价值的方法。     

Guidance laws for attacking defended target

In this paper, two new guidance laws based on differential game theory are proposed and investigated for the attacker in an attacker-defender-target scenario.The conditions for the attacker winning the game are analyzed when the target and defender using the differential game guidance law based on the linear model.The core ideas underlying the two guidance laws are the attacker evading to a critical safe boundary from the defender, and then maintaining a critical miss distance.The guidance law more appropriate for the attacker to win the game differs according to the initial parameters.Unlike other guidance laws, when using the derived guidance laws there is no need to know the target and the defender's control efforts.The results of numerical simulations show that the attacker can evade the defender and hit the target successfully by using the proposed derived guidance laws.     

建设工程项目工期优化分析

分析了传统的工期优化方法存在的不足，考虑建设项目提前投产的经济效益、缩短工期减少承包商固定资产占用带来的效益、缩短工期减少投资项目的固定资产及流动资金的上用时给业主带来的资金时间价值等因素，建立了工期优化的理论模型，与传统的工期——成本优化方法进行了比较分析，并给出了实用的优化方法。     

An Adaptive Weighted Differential Game Guidance Law

For intercepting modern high maneuverable targets, a novel adaptive weighted differential game guidance law based on the game theory of mixed strategy is proposed, combining two guidance laws which are derived from the perfect and imperfect information pattern, respectively. The weights vary according to the estimated error of the target’s acceleration, the guidance law is generated by directly using the estimation of target’s acceleration when the estimated error is small, and a differential game guidance law with adaptive penalty coefficient is implemented when the estimated error is large. The adaptive penalty coefficients are not constants and they can be adjusted with current target maneuverability. The superior homing performance of the new guidance law is verified by computer simulations.     

Stochastic game approach to air operations

A command and control (C/sup 2/) problem for military air operations is addressed. Specifically, we consider C/sup 2/ problems for air vehicles against ground-based targets and defensive systems. The problem is viewed as a stochastic game. We restrict our attention to the C/sup 2/ level where the problem may consist of a few unmanned combat air vehicles (UCAVs) or aircraft (or possibly teams of vehicles), less than say, a half-dozen enemy surface-to-air missile air defense units (SAMs), a few enemy assets (viewed as targets from our standpoint), and some enemy decoys (assumed to mimic SAM radar signatures). At this low level, some targets are mapped out and possible SAM sites that are unavoidably part of the situation are known. One may then employ a discrete stochastic game problem formulation to determine which of these SAMs should optimally be engaged (if any), and by what series of air vehicle operations. We provide analysis, numerical implementation, and simulation for full state-feedback and measurement feedback control within this C/sup 2/ context. Sensitivity to parameter uncertainty is discussed. Some insight into the structure of optimal and near-optimal strategies for C/sup 2/ is obtained. The analysis is extended to the case of observations which may be affected by adversarial inputs. A heuristic based on risk-sensitive control is applied, and it is found that this produces improved results over more standard approaches.     

On Optimal Minimax Jamming and Detection of Radar Signals

A game between an intelligent jammer J and decision maker DM is considered. DM seeks to detect a coherent slowly fading narrowband signal under a Neyman-Pearson criterion. His observations are corrupted with additive narrowband noise, the source of which is J's jamming with a power constraint, but otherwise almost arbitrary statistics. DM knows J's action but the converse is not true. When the number of samples increases asymptotically, a minimax solution for the game exists where the jamming is Gaussian, independent of the desired signal amplitude level and probability distribution. The same result also holds for detection of a nonrandom baseband signal.