基于高斯估算的多智能体最优覆盖控制网络研究

文章主要介绍了多智能体最优覆盖控制的实质就是多智能体在目标区域内的最优分布,提出了一种基于高斯估计的最优覆盖控制网络并通过推导证明其是可实现的,即根据多智能体覆盖网络的相互采样信息,利用高斯估算对目标区域内相应的敏感度进行计算,最终求得多智能体在控制覆盖网络的最优位置。

基于高斯估算的最优覆盖控制在多无人机协同任务规划中应用研究

多无人机协同任务规划是一个复杂的决策与优化问题,它受到环境、任务要求等多种因素影响,本文主要介绍了最优覆盖控制的研究背景和意义,多无人机的最优覆盖控制的实质就是多无人机在目标区域内的协同任务规划的最优配置,文中提出了一种基于高斯估计的最优覆盖控制并通过推导证明其是可实现的,即根据多无人机目标区域的采样信息,使用高斯估算对无人机特定区域内敏感度函数进行计算,最终得到多无人机在协同任务规划的最优方法。

基于模型参考的多自主水下航行器自适应覆盖控制

针对海洋监测过程中由水下粘滞物等因素引起系统模型参数变化的情况,提出了一种基于模型参考的多自主水下航行器(autonomous underwater vehicles,AUV)自适应覆盖控制方法,旨在合理分配多AUV资源,提高目标海域的监测效率。首先根据给出的系统代价函数,应用质心Voronoi分配原则对目标海域进行最优分配,确定多AUV最优监测目标。在此基础上,利用基于模型参考的自适应控制方法,设计在AUV模型参数未知的情况下,多AUV的最优覆盖控制方法,使得覆盖网络能够从任意初始位置收敛到最优覆盖配置。最后通过仿真实验验证了上述算法的可行性与有效性。

Biofumigation for Weed Management in Cabbage

Field studies were conducted in Lebanon to investigate the effect of solarization with/without cover crop green manure on weed population in subsequent planting of cabbage. Cover crops （alfalfa, barley, clover, lathrus and vetch） or crushed olive pulp were planted/added in i 8 m2 plots 75 days prior to planting cabbage. Crops and crushed olive pulps were ploughed under （CCGM） and then half the plots in each treatment were solarized （Biofumigation） by covering each plot with a clear polyethylene sheet for 40 days. Solarization with or without biofumigation significantly reduced weed population in subsequent cabbage planting as compared to nonsolarized CCGM or to the control. Solarization and biofumigation significantly increased fresh weight of cabbage as compared to the control and to nonsolarized CCGM treatments. Optimal weed control was observed in plots which were biofumigated with clover as a CCGM,