一类非线性参数化系统的鲁棒自适应H_∞控制

针对一类带有未知虚拟控制系数的非线性参数化系统,利用参数分离技术和Backstepp ing设计方法构造自适应H?控制器,使闭环系统的干扰输入在L2增益下对系统输出的影响任意小,且无外扰时,系统内稳.仿真例子验证了主要结论.     

改进萤火虫算法及其收敛性分析

萤火虫算法因具有结构简单、控制参数少、易于实现的特点而得到广泛的关注和应用,但其易陷入局部最优导致过早收敛,从而影响寻优精度。针对这一问题,本文在位置更新规则中加入随机扰动因子,并剔除了冗余的随机项,以提高算法搜索能力;引入位置置换变异和差分进化算法中的最优变异策略,在保持种群多样性的同时,增强算法跳出局部最优的能力。采用马尔可夫过程证明了算法以概率1收敛到全局最优。利用基准函数和装箱问题对算法进行仿真测试,结果表明,改进后的算法能够有效跳出局部最优,对给出的所有问题均能找到理论最优解,寻优精度和成功率有明显提升。     

一类径向基神经网络干扰观测器轨迹线性化控制

利用径向基神经网络(RBFNN)的逼近能力,研究了基于径向基神经网络干扰观测器(RDO)的鲁棒自适应轨迹线性化控制(TLC)策略,以解决空天飞行器复杂飞行条件下系统不确定及干扰的控制问题。分析了系统存在不确定性时轨迹线性化控制方法性能降低甚至失效的原因,设计了自适应调节律,并采用Lyapunov方法严格证明了在该自适应调节律作用下闭环系统所有误差信号最终有界。仿真结果表明,较当前TLC方法的控制性能,新方案在空天飞行器系统上具有更优异的控制性能和鲁棒性。     

扰动累积下基于数字孪生的车间重调度

针对隐性扰动累积下车间重调度问题,搭建车间重调度决策服务,实现数字孪生驱动的扰动累积下的车间重调度。提出一种调度参数更新的方式,采用随机概率分布来描述调度参数的分布,提升调度参数的准确性;利用孪生网络搭建隐性扰动检测模型,以实时数据为输入,实现重调度的启动时刻的判定;从历史调度数据中提取用于调度知识挖掘的样本数据,利用伪孪生网络获取工序和机器的状态数据的映射关系作为调度规则,用于车间的重调度。仿真实验证明了所提数字孪生驱动的重调度模式的可行性。     

排水板施工对软黏土扰动的现场试验研究

通过软黏土地基上塑料排水板施工过程的孔隙水压力观测及现场十字板强度试验,研究了排水板施工前后地基土体孔隙水压力增长和消散的规律,并且从软黏土地基的有效应力变化和结构扰动等方面分析了土体强度损失及恢复过程.结果表明:单根排水板施工引起的孔隙水压力增长较小,仅对表层孔隙水压力影响大;板群的施工对4 m范围内土体孔隙水压力的增长有叠加效应;排水板施工一方面使软土地基内的孔隙水压力增长,有效应力减小,导致软土强度的降低,另一方面使地基软土结构发生破坏而引起软土强度降低;孔隙水压力的增长引起的地基土强度损失恢复较快,而结构扰动引起的强度损失恢复较慢.     

概率统计观念形成中的思维障碍分析

概率统计的研究对象是随机现象.概率统计思维的本质在于:对随机事件发生的频繁程度定量化,在不确定的情景中作出良好判断.正是其思维方法别具一格,学生理解概率显得很复杂、很困难.通过对具体概率统计问题常见错误的分析,发现概率统计观念形成中的思维障碍,提出概率统计教学中应关注的方面.     

Patterns of artificial avian nest predation by introduced rats in a fragmented laurel forest (Tenerife,Canary Islands)

The importance of introduced rats as damaging factors on island biotas is globally recognized. The predation of artificial avian nests by Ship rats (Rattus rattus) in fragmented laurel forests in Tenerife (Canary Islands) was explored. The influence of road edge, patch type, and position (ground versus tree) on nest survival in two forest remnants differing in conservation degree, were assessed using failure‐time analysis. Overall, nest predation was greater in the preserved than in the disturbed remnant. Nest predation also differed among and within patches, variation being greater within the disturbed remnant. The probability of nest failure was higher at the interior than along the road edge in both remnants, but the road edge effect on nest predation was more intense in the disturbed remnant. Predation pressure was higher in patches of mature, closed canopy or dense understorey with stump sprouting. Ground nests were predated at higher rates than tree nests at any location. These results contrast with other nest predation studies in fragmented landscapes where forest edges rather than the interior are more frequently used by predators. Predatory activity by rats seems negatively affected by forest disturbance and road edge effect. Overall, artificial nest predation patterns by rats confirm a potential predation risk for the avifauna of the Canarian laurel forest. This should be considered in implementing conservation management programmes.     

抗干扰的MRAC系统设计

基于popov超稳定理论提出一种新的抗干扰的模型参考自适应控制方案,不需要对干扰作任何的假设与近似.通过引入几种特定形式的干扰进行仿真,仿真结果表明了该方案的有效性.     

直升机/发动机综合控制的发展及技术特点

对直升机/发动机（简称直/发）综合控制技术的研究需求、发展及现状进行了归纳和分析，讨论了直/发综合抗扰控制与优化控制的方案选择、 技术特点和研究动向，其中着重分析了基于扭矩前馈控制、自适应燃油控制、自抗扰控制、预测控制等手段的综合抗扰控制，以及包含最小油耗、最大功率、最低涡轮温度优化模式的综合优化控制的研究和应用情况. 最后，在总结全文的基础上，提出今后在直/发综合控制研究工作中值得关注的一些问题.     

Prediction from the One‐Way Error Components Model with AR(1) Disturbances

In this paper we extend the works of Baillie and Baltagi (1999, in Analysis of Panels and Limited Dependent Variables Models, Hsiao C et al. (eds). Cambridge University Press: Cambridge, UK; 255–267) and generalize certain results from the Baltagi and Li (1992, Journal of Forecasting 11 : 561–567) paper accounting for AR(1) errors in the disturbance term. In particular, we derive six predictors for the one‐way error components model, as well as their associated asymptotic mean squared error of multi‐step prediction in the presence of AR(1) errors in the disturbance term. In addition, we also provide both theoretical and simulation evidence as to the relative efficiency of our alternative predictors. The adequacy of the prediction AMSE formula is also investigated by the use of Monte Carlo methods and indicates that the ordinary optimal predictor performs well for various accuracy criteria. Copyright © 2011 John Wiley & Sons, Ltd.