A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear cont...A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear continuous switch function.The proposed new friction model solves the implementation problems with the traditional LuGre model at high speeds.An improved artificial fish swarm algorithm(IAFSA)method which combines the chaotic search and Gauss mutation operator into traditional artificial fish swarm algorithm is used to identify the parameters in the proposed modified LuGre friction model.The steady state response experiments and dynamic friction experiments are implemented to validate the effectiveness of IAFSA algorithm.The comparisons between the measured dynamic friction forces and the ones simulated with the established mathematic friction model at different frequencies and magnitudes demonstrate that the proposed modified LuGre friction model can give accurate simulation about the dynamic friction characteristics existing in the electromagnetic valve actuator system.The presented modelling and parameter identification methods are applicable for many other high-speed mechanical systems with friction.展开更多
We introduce the artificial fish swarm algorithm for heading motion model identification and control parameter optimization problems for the“Ocean Rambler”unmanned wave glider(UWG).First,under certain assumptions,th...We introduce the artificial fish swarm algorithm for heading motion model identification and control parameter optimization problems for the“Ocean Rambler”unmanned wave glider(UWG).First,under certain assumptions,the rigid-flexible multi-body system of the UWG was simplified as a rigid system composed of“thruster+float body”,based on which a planar motion model of the UWG was established.Second,we obtained the model parameters using an empirical method combined with parameter identification,which means that some parameters were estimated by the empirical method.In view of the specificity and importance of the heading control,heading model parameters were identified through the artificial fish swarm algorithm based on tank test data,so that we could take full advantage of the limited trial data to factually describe the dynamic characteristics of the system.Based on the established heading motion model,parameters of the heading S-surface controller were optimized using the artificial fish swarm algorithm.Heading motion comparison and maritime control experiments of the“Ocean Rambler”UWG were completed.Tank test results show high precision of heading motion prediction including heading angle and yawing angular velocity.The UWG shows good control performance in tank tests and sea trials.The efficiency of the proposed method is verified.展开更多
准确的出行端点信息采集是保障交通规划方案有效性的重要基础。4G/5G通信技术能够连续、动态追踪个体全过程出行轨迹,为精细化出行端点采集带来了新契机。然而手机信令数据固有的不均匀时空定位特性对出行端点识别效果造成了巨大挑战,...准确的出行端点信息采集是保障交通规划方案有效性的重要基础。4G/5G通信技术能够连续、动态追踪个体全过程出行轨迹,为精细化出行端点采集带来了新契机。然而手机信令数据固有的不均匀时空定位特性对出行端点识别效果造成了巨大挑战,本文提出一种适用于手机信令不均匀时空定位轨迹的自适应出行端点识别方法。首先,构建U-DBSCAN(Uneven Positioning Density Based Spatial Clustering of Applications with Noise)算法用于不同密度数据下个体出行端点识别,该算法同步考虑信令数据时空双重不均匀约束特性,可有效弥补稀疏信令数据造成的停留点漏识别和错误识别问题;其次,基于K-平均最近邻算法建立U-DBSCAN参数自适应协同框架,实现了数据密度可调可变环境下模型参数自适应最优匹配,促进出行端点识别效果与技术普适性提升。在贵阳市开展大量同步对比实证试验,结果表明:不均匀时空定位环境下个体出行端点识别精度达90.98%,平均坐标误差为344.13 m,出行端点到达与离开时间误差均小于3 min;相较于KANN-DBSCAN(K-Average Nearest Neighbor Density Based Spatial Clustering of Applications with Noise)、ST-DBSCAN(Spatial Temporal Density Based Spatial Clustering of Applications with Noise)和DBSCAN(Density Based Spatial Clustering of Applications with Noise)等算法,准确率提升9.62%~23.45%,说明本文方法的精确性和稳定性更佳。本文能够为分析居民出行活动与需求特征,提升交通规划方案有效性提供有力支撑。展开更多
基金Project(2015BAG06B00)supported by the National Key Technology Research from Development Program of the Ministry of Science and Technology of China
文摘A new modified LuGre friction model is presented for electromagnetic valve actuator system.The modification to the traditional LuGre friction model is made by adding an acceleration-dependent part and a nonlinear continuous switch function.The proposed new friction model solves the implementation problems with the traditional LuGre model at high speeds.An improved artificial fish swarm algorithm(IAFSA)method which combines the chaotic search and Gauss mutation operator into traditional artificial fish swarm algorithm is used to identify the parameters in the proposed modified LuGre friction model.The steady state response experiments and dynamic friction experiments are implemented to validate the effectiveness of IAFSA algorithm.The comparisons between the measured dynamic friction forces and the ones simulated with the established mathematic friction model at different frequencies and magnitudes demonstrate that the proposed modified LuGre friction model can give accurate simulation about the dynamic friction characteristics existing in the electromagnetic valve actuator system.The presented modelling and parameter identification methods are applicable for many other high-speed mechanical systems with friction.
基金Project(51779052)supported by the National Natural Science Foundation of ChinaProject(QC2016062)supported by the Natural Science Foundation of Heilongjiang Province,China+2 种基金Project(614221503091701)supported by the Research Fund from Science and Technology on Underwater Vehicle Laboratory,ChinaProject(LBH-Q17046)supported by the Heilongjiang Postdoctoral Funds for Scientific Research Initiation,ChinaProject(HEUCFP201741)supported by the Fundamental Research Funds for the Central Universities,China
文摘We introduce the artificial fish swarm algorithm for heading motion model identification and control parameter optimization problems for the“Ocean Rambler”unmanned wave glider(UWG).First,under certain assumptions,the rigid-flexible multi-body system of the UWG was simplified as a rigid system composed of“thruster+float body”,based on which a planar motion model of the UWG was established.Second,we obtained the model parameters using an empirical method combined with parameter identification,which means that some parameters were estimated by the empirical method.In view of the specificity and importance of the heading control,heading model parameters were identified through the artificial fish swarm algorithm based on tank test data,so that we could take full advantage of the limited trial data to factually describe the dynamic characteristics of the system.Based on the established heading motion model,parameters of the heading S-surface controller were optimized using the artificial fish swarm algorithm.Heading motion comparison and maritime control experiments of the“Ocean Rambler”UWG were completed.Tank test results show high precision of heading motion prediction including heading angle and yawing angular velocity.The UWG shows good control performance in tank tests and sea trials.The efficiency of the proposed method is verified.
文摘准确的出行端点信息采集是保障交通规划方案有效性的重要基础。4G/5G通信技术能够连续、动态追踪个体全过程出行轨迹,为精细化出行端点采集带来了新契机。然而手机信令数据固有的不均匀时空定位特性对出行端点识别效果造成了巨大挑战,本文提出一种适用于手机信令不均匀时空定位轨迹的自适应出行端点识别方法。首先,构建U-DBSCAN(Uneven Positioning Density Based Spatial Clustering of Applications with Noise)算法用于不同密度数据下个体出行端点识别,该算法同步考虑信令数据时空双重不均匀约束特性,可有效弥补稀疏信令数据造成的停留点漏识别和错误识别问题;其次,基于K-平均最近邻算法建立U-DBSCAN参数自适应协同框架,实现了数据密度可调可变环境下模型参数自适应最优匹配,促进出行端点识别效果与技术普适性提升。在贵阳市开展大量同步对比实证试验,结果表明:不均匀时空定位环境下个体出行端点识别精度达90.98%,平均坐标误差为344.13 m,出行端点到达与离开时间误差均小于3 min;相较于KANN-DBSCAN(K-Average Nearest Neighbor Density Based Spatial Clustering of Applications with Noise)、ST-DBSCAN(Spatial Temporal Density Based Spatial Clustering of Applications with Noise)和DBSCAN(Density Based Spatial Clustering of Applications with Noise)等算法,准确率提升9.62%~23.45%,说明本文方法的精确性和稳定性更佳。本文能够为分析居民出行活动与需求特征,提升交通规划方案有效性提供有力支撑。
