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Manipulator tracking technology based on FSRUKF
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作者 SHI Guoqing ZHANG Boyan +5 位作者 ZHANG Jiandong YANG Qiming HUANG Xiaofeng QUE Jianyao PU Junwei GENG Xiutang 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2024年第2期473-484,共12页
Aiming at the shortcoming that the traditional industrial manipulator using off-line programming cannot change along with the change of external environment,the key technologies such as machine vision and manipulator ... Aiming at the shortcoming that the traditional industrial manipulator using off-line programming cannot change along with the change of external environment,the key technologies such as machine vision and manipulator control are studied,and a complete manipulator vision tracking system is designed.Firstly,Denavit-Hartenberg(D-H)parameters method is used to construct the model of the manipulator and analyze the forward and inverse kinematics equations of the manipulator.At the same time,a binocular camera is used to obtain the threedimensional position of the target.Secondly,in order to make the manipulator track the target more accurately,the fuzzy adaptive square root unscented Kalman filter(FSRUKF)is proposed to estimate the target state.Finally,the manipulator tracking system is built by using the position-based visual servo.The simulation experiments show that FSRUKF converges faster and with less error than the square root unscented Kalman filter(SRUKF),which meets the application requirements of the manipulator tracking system,and basically meets the application requirements of the manipulator tracking system in the practical experiments. 展开更多
关键词 square root unscented kalman filter(SRUKF) fuzzy inference MANIPULATOR visual servo
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基于均方根容积卡尔曼滤波的船舶操纵运动响应模型参数辨识
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作者 李晴昊 任俊生 华焱 《系统仿真学报》 CAS 2024年第8期1790-1799,共10页
为了解决扩展卡尔曼滤波(extended Kalman filter,EKF)算法在船舶操纵运动模型参数辨识中存在辨识精度低、稳定性差和泛化能力弱的问题,提出了一种基于均方根容积卡尔曼滤波(square root cubature Kalman filter,SRCKF)的辨识算法。在CK... 为了解决扩展卡尔曼滤波(extended Kalman filter,EKF)算法在船舶操纵运动模型参数辨识中存在辨识精度低、稳定性差和泛化能力弱的问题,提出了一种基于均方根容积卡尔曼滤波(square root cubature Kalman filter,SRCKF)的辨识算法。在CKF框架下将方差矩阵的均方根代替原始方差矩阵,使用三角分解对其进行预测和更新以提高辨识的稳定性。将EKF作为对比算法,利用四阶龙格库塔法解算的数值仿真数据,对舵角符合舵机伺服机构变化的船舶二阶非线性响应模型参数进行辨识,并将得到的辨识模型开展泛化能力验证试验。结果表明:SRCKF算法具有比EKF算法更高的辨识精度、稳定性和泛化能力。 展开更多
关键词 参数辨识 SRCKF(square root cubature kalman filter) 四阶龙格库塔法 舵机伺服机构 响应模型
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