如何使大学英语课堂更具吸引力

本文探讨了学生上英语课的动机，教师在课堂教学中究竟起到什么作用。以及如何根据学生的要求，教师来充分展示英语课堂的魅力，使它富于变化，充满活力，把更多的学生吸引到课堂上来，改善学生的出勤率。     

分散式多点优化算法及其在多段翼型气动优化中的应用

论述了一种基于基因算法与博弈论的分散式多点优化算法，并应用于多段翼型的气动优化。基因算法是在计算机中模拟自然进化的随机优化算法，随着科学技术的发展，越来越多的优化问题趋向于多目标优化，这就使得结合博弈论以寻求高效优化算法成为必然。本文分别构造了Nash策略及Stackelberg策略与基因算法结合的分散式多点优化算法，应用于多段翼型高升力气动优化，得到了数值结果，并与实验结果进行了对比。     

Mission decision-making method of multi-aircraft cooperatively attacking multi-target based on game theoretic framework

Coordinated mission decision-making is one of the core steps to effectively exploit the capabilities of cooperative attack of multiple aircrafts. However, the situational assessment is an essential base to realize the mission decision-making. Therefore, in this paper, we develop a mission decision-making method of multi-aircraft cooperatively attacking multi-target based on situational assessment. We have studied the situational assessment mathematical model based on the Dempster-Shafer (D-S) evidence theory and the mission decision-making mathematical model based on the game theory. The proposed mission decision-making method of antagonized airfight is validated by some simulation examples of a swarm of unmanned combat aerial vehicles (UCAVs) that carry out the mission of the suppressing of enemy air defenses (SEAD).     

基于模糊理论的微分对策制导律

在现代战场环境下，导弹制导所需信息经常受到各种干扰，有时甚至是不确定的。而基于精确模型的微分对策制导律的实时实现面临着许多困难。为解决这个问题，尝试将模糊理论与微分策制导律相结合，采用多级模糊控制规则，以导弹怀收音机格半为例，给出了模型的建立方法，并探讨了这种模糊微分对策制导律实现的可行性和优点，为将来发展基于微分对策理论的智能制导律提供了一定的思路。     

Optimal trajectory and downlink power control for multi-type UAV aerial base stations

Unmanned Aerial Vehicles (UAVs) enabled Aerial Base Stations (UABSs) have been studied widely in future communications. However, there are a series of challenges such as interference management, trajectory design and resource allocation in the scenarios of multi-UAV networks. Besides, different performances among UABSs increase complexity and bring many challenges. In this paper, the joint downlink transmission power control and trajectory design problem in multi-type UABSs communication network is investigated. In order to satisfy the signal to interference plus noise power ratio of users, each UABS needs to adjust its position and transmission power. Based on the interactions among multiple communication links, a non-cooperative Mean-Field-Type Game (MFTG) is proposed to model the joint optimization problem. Then, a Nash equilibrium solution is solved by two steps: first, the users in the given area are clustered to get the initial deployment of the UABSs; second, the Mean-Field Q (MFQ)-learning algorithm is proposed to solve the discrete MFTG problem. Finally, the effectiveness of the approach is verified through the simulations, which simplifies the solution process and effectively reduces the energy consumption of each UABS.     

Linear-quadratic and norm-bounded differential game combined guidance strategy against active defense aircraft in three-player engagement

A new type of guidance strategy, combining linear quadratic and norm-bounded game theory, is proposed for the scenario of an attacker against active defense aircraft in three-player engagement. The problem involves three players, an attacker, a defender and a target. The differential game theory and the solution of Hamiltonian equation are utilized to obtain the combined guidance strategy for each player with arbitrary-order dynamics. The game process is divided into 4 phases, C1-C4, according to the switching time. The linear quadratic differential game guidance scheme is employed to reduce the fuel cost in the game parts of C1 and C3. The norm-bounded game guidance strategy is adopted to satisfy the constraint of control input in the game stages C2 and C4. Furthermore, zero-effort miss distance is introduced to meet the constraints of game space and defender’s killing radius in the guidance strategy, which guarantees that the attacker is able to avoid the interception of the defender and hit the target with lower fuel cost and maximum acceleration. And it is proved that the proposed guidance strategy satisfies the Nash equilibrium condition. Finally, the feasibility and superiority of combined guidance strategy are respectively illustrated by nonlinear numerical simulation and verified by comparing with linear quadratic and norm-bounded differential game guidance strategies.     

基于UAV的空地协同任务卸载策略研究

随着各行业对大批量信息处理需求的增加，移动边缘计算（Mobile Edge Computing， MEC）技术应运而生。而在陆地障碍较多、MEC服务器搭载不便的情况下，研究了一种无人机（Unmanned Aerial Vehicle， UAV）中继辅助用户卸载任务到基站的场景。针对该场景，提出了一种基于博弈论的最优任务卸载方法，通过联合优化任务卸载比例和卸载策略使得系统时延最小化。由于这两个变量之间相互耦合，因此将原优化问题转化为两个子问题求解。首先，在确定策略的情况下，证明了系统时延最小值存在的条件，得到了用户的最优卸载比例闭合解。然后，将原优化问题转化为任务分配问题，并建立博弈论模型。在证明了该模型存在纳什均衡（Nash Equilibrium，NE）的前提下，经过多次迭代，求解得到基于时延最小的用户任务卸载策略集。仿真结果表明：上述方法有效降低了全局计算时延，在时效性上优于其他一些常见的卸载方法。