基于显式表达式的空间目标最大碰撞概率分析

最大碰撞概率的计算在空间目标碰撞风险评估中具有重要意义。基于碰撞概率的显式 表达式,利用一元函数和二元函数求极值的方法分别讨论了目标误差椭球形状固定和不定两 种情况下最大碰撞概率的计算方法,得到了两种情况下最大碰撞概率的表达式。对于误差椭 球形状固定的情况得到了碰撞概率最大时两目标位置协方差的取值,对于误差椭球不定情况 得到了碰撞概率最大时径向联合方差的取值和水平面内联合方差所满足的关系。分析了最大 碰撞概率的影响因素,讨论了水平面内误差方差的耦合特性。对今年二月发生的美俄卫星碰 撞事件进行了分析,得到误差椭球任意形状时最大碰撞概率为1.864E-3。
     

Obstacle avoidance handling and mixed integer predictive control for space robots

This paper presents a novel obstacle avoidance constraint and a mixed integer predictive control (MIPC) method for space robots avoiding obstacles and satisfying physical limits during performing tasks. Firstly, a novel kind of obstacle avoidance constraint of space robots, which needs the assumption that the manipulator links and the obstacles can be represented by convex bodies, is proposed by limiting the relative velocity between two closest points which are on the manipulator and the obstacle, respectively. Furthermore, the logical variables are introduced into the obstacle avoidance constraint, which have realized the constraint form is automatically changed to satisfy different obstacle avoidance requirements in different distance intervals between the space robot and the obstacle. Afterwards, the obstacle avoidance constraint and other system physical limits, such as joint angle ranges, the amplitude boundaries of joint velocities and joint torques, are described as inequality constraints of a quadratic programming (QP) problem by using the model predictive control (MPC) method. To guarantee the feasibility of the obtained multi-constraint QP problem, the constraints are treated as soft constraints and assigned levels of priority based on the propositional logic theory, which can realize that the constraints with lower priorities are always firstly violated to recover the feasibility of the QP problem. Since the logical variables have been introduced, the optimization problem including obstacle avoidance and system physical limits as prioritized inequality constraints is termed as MIPC method of space robots, and its computational complexity as well as possible strategies for reducing calculation amount are analyzed. Simulations of the space robot unfolding its manipulator and tracking the end-effector’s desired trajectories with the existence of obstacles and physical limits are presented to demonstrate the effectiveness of the proposed obstacle avoidance strategy and MIPC control method of space robots.     

自由漂浮空间机器人多约束混合整数预测控制

针对空间机器人完成任务时需要躲避障碍物的问题,提出一种自由漂浮空间机器人的混合整数预测控制方法。首先,在模型预测控制方法框架下,机械臂关节的物理限制,躲避障碍物的要求被统一描述为最优控制问题下的不等式约束,可以得到自由漂浮空间机器人具有线性二次规划形式的最优控制律。其次,基于命题逻辑建立控制问题中各约束的优先级,保证在最大程度地满足约束的情形下得到控制问题的解,有效弥补了模型预测控制方法用于空间机器人控制时,多约束可能导致最优控制问题不可行的不足。最后,仿真结果校验了所设计控制律的有效性。     

Chicks incubated in hypomagnetic field need more exogenous noradrenaline for memory consolidation

The geomagnetic field (GMF) is one of the essential characteristics of the terrestrial environment but does not apply in outer space. The elimination of GMF may interfere with the normal activities of life in many aspects. Previous behavioral experiments have found that long-term memory is impaired in chicks incubated in a near-zero magnetic environment (i.e. hypomagnetic field or HMF). The present study was designed to evaluate the possible involvement of noradrenergic change in the functional abnormality observed before. A HMF space was produced by nullifying the natural GMF with three pairs of Helmholtz coils. The one-trial passive avoidance learning paradigm was performed on day-old chicks incubated in either the HMF space or the natural GMF. Exogenous noradrenaline was administered by intracerebral injections and the effect on memory consolidation was compared between the two categories of subjects. In the behavioral paradigm, the HMF chicks had a higher elimination rate than the GMF chicks and displayed a significant reduction in overall responsiveness. The administration of moderate doses (0.1–0.5 nmol/hemisphere) of noradrenaline led to fairly good memory retention in GMF chicks but had little effect on HMF chicks. However, long-term memory of HMF chicks could be elevated to the normal level by much higher doses (1.0–1.75 nmol/hem) of the drug. These results suggest that prolonged exposure to HMF may induce disorders in the noradrenergic system in the brain and indicate a potentiality of counteracting the ill-effect of GMF deprivation with appropriate pharmacological manipulation.     

编队卫星防碰撞规避路径规划方法与控制研究

针对编队卫星在构型重构和构型失效重组时发生碰撞可能性最大的两种机动工况,采用数学规划的方法对其进行防碰撞规避准则、规避策略和控制方面的研究;并通过系统可控性证明出无径向推力相对于全向推力,也可以达到目标相位点只是燃料消耗得多。对编队构型失效重组工况中备份星机动前停泊位置,进入编队位置选择和启动时刻选择以及故障星离开编队后,目标轨道确定等问题通过数学仿真的形式予以解答。仿真结果表明,该研究方法真实可信、简便有效。     

兼顾控制流量的软件定义卫星网络路由策略

软件定义卫星网络（SDSN）通过解耦数据与控制平面,实现网络态势与控制的逻辑集中,为管理卫星网络提供了一种新的思路。在SDSN中,控制报文和数据报文同时在网络中传输,海量、动态、高优先级的控制流量将对数据报文传输产生极大的干扰。因此,提出了一种数据流退让路由（DFRR）策略。在计算数据报文路由时,DFRR将链路上控制流量大小作为影响链路代价的一个因素,以减少选择控制流量较大的链路;在网络操作控制中心（NOCC）连接的过顶卫星切换导致控制流量分布发生较大变化之前,DFRR预测可能发生拥塞的链路,并选出链路上部分数据流进行重路由,从而避免拥塞。在开发的SDSN研究平台OpenSatNet上对DFRR的性能进行了评估。实验结果表明,DFRR能够有效减少网络中的链路拥塞,以及控制报文和数据报文的分组丢失。      

基于超声模糊避障算法的移动机器人导航

提出了一种在移动机器人导航中基于多超声传感器的模糊避障算法。利用MATLAB资源设计出模糊控制器,介绍了模糊规则与非模糊化,并给出一种在VC环境下直接调用模糊控制器的方法,改变了以往需要通过查表方式实现模糊控制的模式,大幅提高二次开发能力。在仿真和真实环境下,实验结果都表明该算法有效,能够实现不同环境中的避障任务。     

基于元胞传输模型的实时交通信息设计

随着智能交通技术的发展,可变信息标志(VMS,Variable Message Signs)被广泛应用于动态交通管理中.元胞传输模型(CTM,Cell Transmission Model)可以很好地模拟交通流激波、排队形成与消散等交通流动力学特性.提出一种新的基于CTM的路径行驶时间计算方法,并使用LOGIT原则计算路径选择概率,针对重复性拥挤和非重复性拥挤2种交通状况,分析了VMS对交通流的影响.数值模拟结果表明,理论模型能够合理反映现实的交通状况:发生重复性拥挤时,VMS能够合理疏导人们的出行,减缓交通拥挤;而发生非重复性拥挤时,VMS对高需求和低需求情形下的交通流影响相似,但在高需求情形下,路径选择对模型参数的敏感区很小.