In order to solve the current situation that unmanned aerial vehicles(UAVs)ignore safety indicators and cannot guarantee safe operation when operating in low-altitude airspace,a UAV route planning method that consider...In order to solve the current situation that unmanned aerial vehicles(UAVs)ignore safety indicators and cannot guarantee safe operation when operating in low-altitude airspace,a UAV route planning method that considers regional risk assessment is proposed.Firstly,the low-altitude airspace is discretized based on rasterization,and then the UAV operating characteristics and environmental characteristics are combined to quantify the risk value in the low-altitude airspace to obtain a 3D risk map.The path risk value is taken as the cost,the particle swarm optimization-beetle antennae search(PSO-BAS)algorithm is used to plan the spatial 3D route,and it effectively reduces the generated path redundancy.Finally,cubic B-spline curve is used to smooth the planned discrete path.A flyable path with continuous curvature and pitch angle is generated.The simulation results show that the generated path can exchange for a path with a lower risk value at a lower path cost.At the same time,the path redundancy is low,and the curvature and pitch angle continuously change.It is a flyable path that meets the UAV performance constraints.展开更多
文章考虑了三向叉车在装载货物运行的情况下,其货叉带动货物旋转引起整车的合成重心变化,进而提出一种考虑货物旋转情况的叉车横向稳定性模型。针对三向叉车的合成重心变化导致其横向稳定性不足的问题,首先在该文建立的叉车模型基础上...文章考虑了三向叉车在装载货物运行的情况下,其货叉带动货物旋转引起整车的合成重心变化,进而提出一种考虑货物旋转情况的叉车横向稳定性模型。针对三向叉车的合成重心变化导致其横向稳定性不足的问题,首先在该文建立的叉车模型基础上运用线性二次型调节器(linear quadratic regulator,LQR)最优控制法,提出一种基于天牛须搜索的粒子群算法(particle swarm optimization based on beetle antennae search,BAS-PSO)来优化LQR状态矩阵加权系数的方法,进而设计LQR转向控制器;然后基于BAS-PSO优化的LQR转向控制器实现对理想横摆角速度和理想质心侧偏角的快速跟随;最后在双移线换道工况下进行仿真分析,验证了上述控制策略能有效抑制质心侧偏角的偏移,更好地实时跟踪理想横摆角速度,三向叉车在其货叉装载货物进行旋转操作时的横向稳定性得到了明显改善。展开更多
为了减小局部遮阴情况PSC(partial shading condition)下光伏系统的功率失配损失,提高最大功率点追踪MPPT(maximum power point tracking)的追踪速度和准确性,提出了基于天牛群优化BSO(beetle swarm optimiza?tion)算法的MPPT控制方法....为了减小局部遮阴情况PSC(partial shading condition)下光伏系统的功率失配损失,提高最大功率点追踪MPPT(maximum power point tracking)的追踪速度和准确性,提出了基于天牛群优化BSO(beetle swarm optimiza?tion)算法的MPPT控制方法.把由天牛须搜索BAS(beetle antennae search)借鉴粒子群的群体优化思想而得到的BSO方法应用到MPPT控制,利用天牛的个体进化和群体学习等优势来提高MPPT的追踪速度和精确度.设置了多种光照情况来作仿真验证,并用粒子群方法进行比较分析.结果表明,所提的方法追踪速度更快、精确度更高,且追踪过程更稳定、功率波动较小.展开更多
为提高清洁能源利用率、降低高渗透率可再生能源型微网成本,基于分时电价背景,在综合考虑风电、光伏、燃气轮机、大电网联络线等多类型电源运行特性的基础上,以经济成本为目标,建立了冷热电联供(combined cooling,heating and power,CC...为提高清洁能源利用率、降低高渗透率可再生能源型微网成本,基于分时电价背景,在综合考虑风电、光伏、燃气轮机、大电网联络线等多类型电源运行特性的基础上,以经济成本为目标,建立了冷热电联供(combined cooling,heating and power,CCHP)型微网协同优化模型,同时提出一种结合粒子群思想、协同进化理论框架和天牛须搜索(beetle antennae search,BAS)算法的改进优化算法——CoPSO-BAS算法。该算法同时兼顾了BAS算法、协同进化算法与粒子群算法的优点,具有良好的全局最优解搜索能力与收敛性。以我国西北某微网系统作为实际算例,应用CoPSO-BAS算法进行计算,并与经典BAS算法对比,验证了CoPSO-BAS算法的全局最优解搜索能力和收敛性能上的优越性。展开更多
基金supported by the National Natural Science Foundation of China(61601497)the Natural Science Basic Research Plan in Shaanxi Province of China(2022JM-412)the Air Force Engineering University Principal Fund(XZJ2020005).
文摘In order to solve the current situation that unmanned aerial vehicles(UAVs)ignore safety indicators and cannot guarantee safe operation when operating in low-altitude airspace,a UAV route planning method that considers regional risk assessment is proposed.Firstly,the low-altitude airspace is discretized based on rasterization,and then the UAV operating characteristics and environmental characteristics are combined to quantify the risk value in the low-altitude airspace to obtain a 3D risk map.The path risk value is taken as the cost,the particle swarm optimization-beetle antennae search(PSO-BAS)algorithm is used to plan the spatial 3D route,and it effectively reduces the generated path redundancy.Finally,cubic B-spline curve is used to smooth the planned discrete path.A flyable path with continuous curvature and pitch angle is generated.The simulation results show that the generated path can exchange for a path with a lower risk value at a lower path cost.At the same time,the path redundancy is low,and the curvature and pitch angle continuously change.It is a flyable path that meets the UAV performance constraints.
文摘文章考虑了三向叉车在装载货物运行的情况下,其货叉带动货物旋转引起整车的合成重心变化,进而提出一种考虑货物旋转情况的叉车横向稳定性模型。针对三向叉车的合成重心变化导致其横向稳定性不足的问题,首先在该文建立的叉车模型基础上运用线性二次型调节器(linear quadratic regulator,LQR)最优控制法,提出一种基于天牛须搜索的粒子群算法(particle swarm optimization based on beetle antennae search,BAS-PSO)来优化LQR状态矩阵加权系数的方法,进而设计LQR转向控制器;然后基于BAS-PSO优化的LQR转向控制器实现对理想横摆角速度和理想质心侧偏角的快速跟随;最后在双移线换道工况下进行仿真分析,验证了上述控制策略能有效抑制质心侧偏角的偏移,更好地实时跟踪理想横摆角速度,三向叉车在其货叉装载货物进行旋转操作时的横向稳定性得到了明显改善。
文摘为了减小局部遮阴情况PSC(partial shading condition)下光伏系统的功率失配损失,提高最大功率点追踪MPPT(maximum power point tracking)的追踪速度和准确性,提出了基于天牛群优化BSO(beetle swarm optimiza?tion)算法的MPPT控制方法.把由天牛须搜索BAS(beetle antennae search)借鉴粒子群的群体优化思想而得到的BSO方法应用到MPPT控制,利用天牛的个体进化和群体学习等优势来提高MPPT的追踪速度和精确度.设置了多种光照情况来作仿真验证,并用粒子群方法进行比较分析.结果表明,所提的方法追踪速度更快、精确度更高,且追踪过程更稳定、功率波动较小.
