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首页> 外文期刊>Proceedings of the Institution of Mechanical Engineers, Part C. Journal of mechanical engineering science >Experimental kinematic identification and position control of a 3-DOF decoupled parallel robot
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Experimental kinematic identification and position control of a 3-DOF decoupled parallel robot

机译:实验运动识别和3-DOF解耦并联机器人的位置控制

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摘要

This paper aims at using a kinematic identification procedure in order to enhance the control of a 3-DOF fully decoupled parallel robot, the so-called "Tripteron." From a practical standpoint, manufacture errors lead to some kinematic uncertainties in the robot which cause real kinematic equations of the robot to be different from the theoretical ones. In this paper, using a white box identification procedure, the independence of degrees-of-freedom in the robot is studied. Considering the fact that the kinematic identification of a robotic manipulator requires the position of its end-effector to be known, in this paper "Kinect" sensor, which is a vision-infra red sensor, is utilized to obtain the spatial coordinates of the end-effector. In order to calibrate the Kinect, a novel approach which is based on a neuro-fuzzy algorithm, the so-called "LoLiMoT" algorithm, is used. Moreover, the results of experimentally performing the identification and calibrating approach are used to the end of implementing a closed-loop classic controller for path tracking purposes. Furthermore, the theoretical unidentified model was implemented in a sliding mode robust controller in order to compare the results with classic controller. The comparison reveals that classic controller which uses identified model leads to a better performance in terms of accuracy and control effort with respect to robust controller which is purely based on theoretical model.
机译:本文旨在使用运动识别程序,以增强3-DOF完全解耦并行机器人的控制,所谓的“TRETON”。从实际的角度来看,制造错误导致机器人中的一些运动不确定性,导致机器人的真正运动学方程与理论上的不同。本文采用白盒识别程序,研究了机器人中自由度的独立性。考虑到机器人操纵器的运动鉴定需要已知其末端效应器的位置,在本文中,使用该纸张“Kinect”传感器,其是视觉缺陷的红色传感器,用于获得结束的空间坐标-effector。为了校准Kinect,使用基于神经模糊算法,所谓的“Lolimot”算法的新方法。此外,实验性地执行识别和校准方法的结果用于实现用于路径跟踪目的的闭环经典控制器的结束。此外,理论上未识别的模型在滑动模式稳健控制器中实现,以便将结果与经典控制器进行比较。比较揭示了使用所识别的模型的经典控制器在纯粹基于理论模型的鲁棒控制器方面,在精度和控制力方面导致更好的性能。

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