虚拟人运动中受扰的平衡保持算法

为了更加真实且实时地模拟运动中虚拟人恢复平衡的反应动作,提出一种针对受到外界作用力扰动的虚拟人平衡保持算法.首先通过虚拟人质心位移和速度来判断平衡性;然后借助生物力学的研究成果设计了具有人体特性的虚拟人运动受扰后的平衡保持方法,并用动力学进行模拟,驱动虚拟人完成平衡恢复.实验结果表明:该算法计算效率高,符合人体的生物力学特性,并且具有良好的交互性与较好的视觉效果,适用于虚拟人动画合成.     

基于队列的动态电源管理策略

动态电源管理技术是一项系统级电源优化策略,它通过有选择性的关闭(或者降低性能)空闲的可控设备来降低功耗.在回顾以往系统级动态电源管理策略的基础上,提出了一种基于队列的新型系统级动态电源管理策略,利用队列不但可以提高对于可控模块何时被唤醒时间的预测命中率,并且能够根据不断变化的任务负载情况进行自身的快速调节,以适应不同任务的要求,通过搭建的SkyEye环境进行仿真,结果验证了在性能和节能方面,该方法优于传统方法.     

基于DSOF的网格资源发现模型研究

为了解决传统资源发现机制不能很好地适应网格资源环境的问题,在有效组建网格资源虚拟组织的基础上,提出了资源虚拟组织中联系结点的选取原则和选取算法,通过该算法从具有相同资源类型的联系结点中选出管理结点.联系结点和管理结点之间采用类似二部图的方式进行连接,构成基于动态自组织覆盖架构的网格资源发现模型.从资源发现能力、资源发现效率和系统可扩展性等方面对该模型进行了综合评价,结果显示该模型适合网格资源的特征,在大规模网格系统中能够有效提高资源发现性能,仿真实验验证了该模型的有效性.     

悬索桥主缆初应力对桥梁动力特性的影响

为掌握主缆初应力对桥梁动力特性的影响,以悬索桥为例,采用静力非线性分析方法计算应力变化过程中悬索桥的跨中挠度、缆索轴力及加劲梁的轴力变化;将得到的内力作为结构的预加应力进行有预应力的模态分析. 应用ANSYS软件进行分析,其中有限元建模时采用4种单元类型:空间梁单元BEAM4用于模拟加劲梁和塔;空间杆单元LINK10用于模拟主缆及吊杆;通过设定BEAM4和LINK10单元初应变进行有预应力的模态分析;采用MASS21单元模拟横隔板、吊杆锚固装置和桥面上的栏杆,并分别考虑质量和质量惯性矩的作用. 分析表明,悬索桥主梁竖弯振动频率受主缆初应力的影响较大,而侧弯振动频率和扭转振动频率受此影响较小. 该结果为同类桥梁的动力特性分析提供参考.     

低成本的UTRV三维可视化仿真测试系统设计

相对于常规飞行器,倾转旋翼飞行器原本就对飞控系统有着更高的要求,而其无人化后的产品UTRV(无人倾转旋翼飞行器)对此的需要还要更上一层楼.为了满足开发UTRV飞控系统的需要,有必要开发更加方便的飞控系统仿真测试环境.使用现有货架商品构建了一套UTRV三维可视化仿真测试系统.系统内含可调整的UTRV全飞行包线非线性气动模型,用于提供控制律开发和动态仿真;系统可以方便的替换飞控模块程序进行仿真实验,以此验证控制律;同时,仿真实验全程数据以直观的实时三维视觉仿真方式显示,有利于发现飞控系统缺陷.使用货架商品还大大降低了成本,非常适合中小研究所和大学使用.     

水下刚性壁装药爆炸气泡简化模型和数值仿真

为预测沉底装药水下爆炸产生气泡的最大半径和脉动周期,建立了水下刚性壁上的装药爆炸产生气泡的动力学模型.从Bernoulli方程和能量守恒两个角度推导出描述半球形气泡径向运动的流体动力学方程,通过能量法确定了方程的初始条件.对方程数值求解得到第一脉动周期内气泡半径和径向运动速度随时间变化的曲线.利用ANSYS-AUTODYN软件的高精度Euler-Godunov求解器和计算结果映射技术,建立了水下刚性壁上装药爆炸产生气泡运动的数值仿真模型.计算得到了气泡膨胀、收缩、上浮和脉动压力时程曲线及其几何形状变化规律.理论模型与仿真计算得到的气泡半径、脉动周期和径向运动速度均吻合,说明该理论模型满足工程所需精度要求.     

Supervisory control using variable lookahead policies

This paper deals with the efficient on-line calculation of supervisory controls for discrete event systems (DES's) in the framework of limited lookahead control policies (or LLPs) that we introduced in previous papers. In the LLP scheme, the control action after a given trace of events has been executed is calculated on-line on the basis of anN-step ahead projection of the behavior of the DES. To compute these controls, one must calculate after the execution of each event the supremal controllable sublanguage of a finite language with respect to another finite larger language. In our previous work, we showed how the required supremal controllable sublanguage calculation can be performed by using a backward dynamic programming algorithm over the nodes of the tree representation of these two languages. In this paper, we pursue the same approach for the calculation of LLP controls, but instead we adopt a forward calculation procedure over theN-level tree of interest. This forward procedure improves upon previous work by avoiding the explicit consideration of all the nodes of theN-level tree, while still permitting tree-to-tree recursiveness as enabled events are executed by the system. The forward search ends whenever a control decision can be made unambiguously or whenever the boundary of theN-level tree is reached, whichever comes first. This motivates the name Variable Lookahead Policy (or VLP) for this implementation of the LLP supervisory control scheme. This paper presents a general VLP algorithm and studies the properties of several special cases of it. The paper also discusses the implementation of the VLP algorithms and presents computational results regarding the application of these algorithms to a time-varying DES.     

考虑EV充放电意愿的园区综合能源系统双层优化调度

随着电动汽车的普及度越来越高,工业园区的电动汽车用户日益增多,其充放电行为对园区综合能源系统规划和运行带来极大挑战。本文提出了考虑电动汽车充放电意愿的园区综合能源系统双层优化调度。首先基于动态实时电价、电池荷电量、电池损耗补偿、额外参与激励等因素建立充放电意愿模型,在此基础上得到改进的电动汽车充放电模型;然后,以园区综合能源系统总成本最小和电动汽车充电费用最小为目标建立双层优化调度模型,通过KKT条件将内层模型转化为外层模型的约束条件,从而快速稳定的实现单层模型的求解;最后,进行仿真求解,设置3种不同场景,对比了所提模型与一般充放电意愿模型,验证了文中所提引入EV充放电意愿模型的园区综合能源系统双层优化调度的有效性和可行性,具有一定的经济效益。     

A mathematical model for vehicle routing problem under endogenous uncertainty

In this study, a multistage stochastic programming (SP) model is presented for a variant of single-vehicle routing problem with stochastic demands from a dynamic viewpoint. It is assumed that the actual demand of a customer becomes known only when the customer is visited. This problem falls into the category of SP with endogenous uncertainty and hence, the scenario tree is decision-dependent. Therefore, nonanticipativity of decisions is ensured by conditional constraints making up a large portion of total constraints. Thus, a novel approach is proposed that considerably reduces the problem size without any effect on the solution space. Computational results on some test problems are reported.     

Precise identification of moving vehicular parameters based on improved glowworm swarm optimization algorithm

This paper proposes an indirect method for the identification of moving vehicular parameters using the dynamic responses of the vehicle. The moving vehicle is modelled as 2-DOF system with 5 parameters and 4-DOF system with 12 parameters, respectively. Finite element method is used to establish the equation of the coupled bridge–vehicle system. The dynamic responses of the system are calculated by Newmark direct integration method. The parameter identification problem is transformed into an optimization problem by minimizing errors between the calculated dynamic responses of the moving vehicle and those of the simulated measured responses. Glowworm swarm optimization algorithm (GSO) is used to solve the objective function of the optimization problem. A local search method is introduced into the movement phase of GSO to enhance the accuracy and convergence rate of the algorithm. Several test cases are carried out to verify the efficiency of the proposed method and the results show that the vehicular parameters can be identified precisely with the present method and it is not sensitive to artificial measurement noise.