提出了用于直流控制器比例一积分(proportional plus integral,PI)参数寻优的一种系统化方法。首先根据Bode图求出满足系统稳定性要求的PI参数范围;再对该参数范围按一定步长进行划分,得到有限组PI参数以构成PI参数寻优的样本集;对应每...提出了用于直流控制器比例一积分(proportional plus integral,PI)参数寻优的一种系统化方法。首先根据Bode图求出满足系统稳定性要求的PI参数范围;再对该参数范围按一定步长进行划分,得到有限组PI参数以构成PI参数寻优的样本集;对应每一个样本参数仿真计算控制器的阶跃响应, 并按时间乘绝对误差积分(integral of time multiplied by the absolute value of error,ITAE)准则计算目标函数值;取对应 ITAE目标函数值最小的样本参数为最优PI参数。找到的最优PI参数在工程上可近似认为是全局最优的。根据该方法设计了葛洲坝-南桥直流输电工程中的PI控制器,并通过仿真验证了其有效性。展开更多
Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors.Such factors vary over space and time,making the assessment of soil erosion even more difficult.Empirical erosion ...Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors.Such factors vary over space and time,making the assessment of soil erosion even more difficult.Empirical erosion models such as the Revised Universal Soil Loss Equation (RUSLE) provides a rather simple and yet comprehensive framework for assessing soil erosion and its causative factors.RUSLE considers rainfall (R),topography (LS),soil erodibility (K),cover management (C),and support practice (P) as important factors affecting soil erosion.In the past few years,RUSLE has benefited tremendously from advances in geospatial technologies like Geographic Information System (GIS) and remote sensing.In this paper,an overview of recent developments on the use of these geospatial technologies in deriving individual RUSLE factors is provided,placing an emphasis on related successes and challenges.This review is expected to improve the understanding of the role played by such technologies in deriving RUSLE parameters despite existing challenges.Future research,however,must pay special attention to error assessment of remote sensing-derived RUSLE parameters.展开更多
文摘提出了用于直流控制器比例一积分(proportional plus integral,PI)参数寻优的一种系统化方法。首先根据Bode图求出满足系统稳定性要求的PI参数范围;再对该参数范围按一定步长进行划分,得到有限组PI参数以构成PI参数寻优的样本集;对应每一个样本参数仿真计算控制器的阶跃响应, 并按时间乘绝对误差积分(integral of time multiplied by the absolute value of error,ITAE)准则计算目标函数值;取对应 ITAE目标函数值最小的样本参数为最优PI参数。找到的最优PI参数在工程上可近似认为是全局最优的。根据该方法设计了葛洲坝-南桥直流输电工程中的PI控制器,并通过仿真验证了其有效性。
文摘Soil erosion is a direct product of the complex interactions between natural and anthropogenic factors.Such factors vary over space and time,making the assessment of soil erosion even more difficult.Empirical erosion models such as the Revised Universal Soil Loss Equation (RUSLE) provides a rather simple and yet comprehensive framework for assessing soil erosion and its causative factors.RUSLE considers rainfall (R),topography (LS),soil erodibility (K),cover management (C),and support practice (P) as important factors affecting soil erosion.In the past few years,RUSLE has benefited tremendously from advances in geospatial technologies like Geographic Information System (GIS) and remote sensing.In this paper,an overview of recent developments on the use of these geospatial technologies in deriving individual RUSLE factors is provided,placing an emphasis on related successes and challenges.This review is expected to improve the understanding of the role played by such technologies in deriving RUSLE parameters despite existing challenges.Future research,however,must pay special attention to error assessment of remote sensing-derived RUSLE parameters.
