TVBPS：一种基于Parallel Sets的具有度量属性的多变元时态数据可视化方法

针对现有“具有度量属性的多变元时态数据”可视化方法不足,提出Parallel Sets分类值排列顺序优化算法ACLEARCR、基于相关度的Parallel Sets变元轴配置算法（VABC）、深度信息Parallel Sets（DCPS）共同组成基于Parallel Sets的具有度量属性的多变元时态数据可视化方法TVBPS。使用具体数据集对提出的可视化方法进行实验,获得的视图能够挖掘数据集中的隐含知识,证明了该方法的有效性。TVBPS可视化方法为分析多变元时态数据集提供了有效手段,具有较高的适用性和易用性。     

不同重力环境的空间机械臂自抗扰轨迹跟踪控制

针对空间机械臂在地面装调与空间应用时,由于重力环境变化导致机械臂模型发生变化的问题,提出了一种自抗扰控制算法,用于完成空间机械臂轨迹跟踪控制的任务.该算法通过将系统模型及未知外扰作为系统的总和扰动,并利用扩张状态观测器对该扰动进行观测且给予补偿,从而提高了系统抗扰的性能.当机械臂模型随重力环境变化而发生变化时,使用同一个自抗扰控制器对其末端轨迹进行控制,均能取得较好的控制效果.通过对系统的稳定性进行分析,证明了所设计控制器的有效性.将仿真结果与PD控制及自适应鲁棒控制做比较,结果表明该控制算法不仅能适应机械臂模型的变化而且还能有效抵抗系统的扰动,从而使系统具有较强的鲁棒性.     

基于红外传感原理的无人机姿态测量系统设计

由于红外温度传感器能有效感知天空间的热辐射,并且相比传统姿态测量的传感器具有体积小、重量轻、成本低等特点,设计一种基于红外传感原理的无人机姿态测量系统;该系统以新型的ARM Cortex—M3内核微处理器STM32F103ZET6作为处理单元,通过采集红外传感器的姿态信息,进行姿态解算,进而获得无人机的姿态角;同时分析了太阳干扰对实验的影响。实验测试表明:该姿态测量系统简单实用,性能稳定,精度高,能有效满足一般无人机姿态测量的要求。     

物联网技术在科研量化管理平台中的应用及探索

科研管理的现代化及高效化是社会发展的趋势,将物联网技术集成到科研管理平台中,能达到高效、科学、高效的效果。完善当前科研管理系统的功能,使得平台除基本的管理功能外,同时具备量化积分功能及论文共享机制等功能,为考核、评价及后续工作提供参考数据,适应当前形势下的复杂需求。     

Host microhabitat location by stem-borer parasitoidCotesia flavipes: the role of herbivore volatiles and locally and systemically induced plant volatiles

The origin of olfactory stimuli involved in the host microhabitat location inCotesia flavipes, a parasitoid of stem-borer larvae, was investigated in a Y-tube olfactometer. The response of femaleC. flavipes towards different components of the plant-host complex, consisting of a maize plant infested with two or more larvae of the stem borerChilo partellus, was tested in dualchoice tests. The concealed lifestyle of the stem-borer larvae did not limit the emission of volatiles attractive to a parasitoid. A major source of the attractive volatiles from the plant-host complex was the stem-borer-injured stem, including the frass produced by the feeding larvae. Moreover, the production of volatiles attractive to a parasitoid was not restricted to the infested stem part but occurs systemically throughout the plant. The uninfested leaves of a stem-borer-infested plant were found to emit volatiles that attract femaleC. flavipes. We further demonstrate that an exogenous elicitor of this systemic plant response is situated in the regurgitate of a stem-borer larva. When a minor amount of regurgitate is inoculated into the stem of an uninfested plant, the leaves of the treated plant emit volatiles that attract femaleC. flavipes.     

基于广义预测控制的船舶编队

针对多船舶之间的编队合作问题,对船舶的编队控制进行研究。利用广义预测控制方法在船舶运行中对理想路径曲线进行预测,得出船舶的运动控制策略;通过运用领导-跟随者编队方法,在Cartesian坐标系下建立船舶编队控制模型,基于这种模型建立一系列船舶航迹约束,得到船队跟随者成员的控制策略。同时在船舶运行过程中,加入风浪的扰动,进行模拟仿真,得到船队的运行轨迹。     

泥岩隧道光面爆破的技术参数研究及应用

针对泥岩隧道的特殊性,通过优化光面爆破的爆破参数,讨论泥岩隧道掘进的经济性、安全性。采用预埋振速传感器监测的方式,分析光面爆破对隧道周围岩体的扰动。现场光爆技术应用效果显著,隧道开挖轮廓线内基本未出现超欠挖现象,半孔率达86%以上,爆破进尺提升约15%,孔痕长度基本均匀分布一般都在孔长的66%以上;萨道夫斯基公式的系数K衰减明显、α基本稳定,光爆的振动速度和围岩扰动都得到了有效控制。     

A parametric frequency response method for non-linear time-varying systems

A new parametric frequency response algorithm is introduced to investigate linear and non-linear dynamic systems with time-varying parameters. In the new algorithm the time-varying parameters are regarded as additional inputs of the systems and the non-linear generalised frequency response functions for multi-input-single-output systems are then employed to obtain Zadeh's system functions from a differential equation representation. The parametric frequency response method reveals how the time-varying parameters affect the behaviour of the systems through a time-varying term. The new method can be applied to both linear and non-linear time-varying systems.     

New results on PWARX model identification based on clustering approach

This paper deals with the problem of piecewise auto regressive systems with exogenous input(PWARX) model identification based on clustering solution. This problem involves both the estimation of the parameters of the affine sub-models and the hyper planes defining the partitions of the state-input regression. The existing identification methods present three main drawbacks which limit its effectiveness. First, most of them may converge to local minima in the case of poor initializations because they are based on the optimization using nonlinear criteria. Second, they use simple and ineffective techniques to remove outliers. Third, most of them assume that the number of sub-models is known a priori. To overcome these drawbacks, we suggest the use of the density-based spatial clustering of applications with noise(DBSCAN) algorithm. The results presented in this paper illustrate the performance of our methods in comparison with the existing approach. An application of the developed approach to an olive oil esterification reactor is also proposed in order to validate the simulation results.