摘要
在塔机定位系统中,负载进行三维运动,其运动系统复杂,定位较为困难。针对塔机负载的定位,建立了应用双层最小二乘(double least squares, DLS)法和D-S(DempsterShafer)证据理论与卡尔曼滤波(Kalman filter, KF)相结合的塔机负载定位算法。首先,引入最小二乘法,进行负载在固定三维空间内的坐标定位,并改进最小二乘法为双层最小二乘法,对负载的三维坐标进行粗略估计;然后,应用D-S证据理论将估计信息进行数据融合,得出估计信息对应的权值;最后,将融合后的数据传入卡尔曼滤波算法,进行更高层次的最优估计,从而实现对塔机负载的精确定位。仿真结果表明,所提算法在定位精度和三维动态误差方面均优于对比算法,可实现对塔机负载的精确定位。
In the tower crane positioning system,the load carries out three-dimensional movement,and its motion system is more complex and positioning is more difficult.A tower crane load location algorithm based on double least square method,D-S evidence theory and Kalman filter is established.Firstly,the least squares method is introduced to locate the coordinates of the load in a fixed three-dimensional space,and the least squares method is improved to a double-layer least squares method to roughly estimate the three-dimensional coordinates of the load.Then,the estimated information is fused with the D-S evidence theory to obtain the corresponding weights of the estimated information.Finally,the fused data is transferred to the Kalman filtering algorithm for a higher level of optimal estimation,so as to achieve accurate positioning of tower crane load.Simulation results demonstrate that the proposed algorithm outperforms comparative algorithms in both positioning accuracy and three-dimensional dynamic error,enabling precise positioning of tower crane loads.
作者
温家凯
陈志梅
邵雪卷
张井岗
WEN Jiakai;CHEN Zhimei;SHAO Xuejuan;ZHANG Jinggang(School of Electronic Information Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China)
出处
《控制工程》
北大核心
2025年第9期1666-1672,共7页
Control Engineering of China
基金
山西省重点研发计划项目(202102020101013)
山西省自然科学基金资助项目(201901D111263)
太原科技大学博士研究基金资助项目(20202070)。
