首页> 外文期刊>Journal of Dynamic Systems, Measurement, and Control >Stiffness Analysis and Control of a Stewart Platform-Based Manipulator With Decoupled Sensor-Actuator Locations for Ultrahigh Accuracy Positioning Under Large External Loads
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Stiffness Analysis and Control of a Stewart Platform-Based Manipulator With Decoupled Sensor-Actuator Locations for Ultrahigh Accuracy Positioning Under Large External Loads

机译:基于Stewart平台的机械手的刚度分析和控制,该机械手具有分离的传感器-执行器位置,可在大外部负载下实现超高精度定位

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Robot frame compliance has a large negative effect on the global accuracy of the system when large external forces/torques are exerted. This phenomenon is particularly problematic in applications where the robot is required to achieve ultrahigh (micron level) accuracy under very large external loads, e.g., in biomechanical testing and high precision machining. To ensure the positioning accuracy of the robot in these applications, the authors proposed a novel Stewart platform-based manipulator with decoupled sensor-actuator locations. The unique mechanism has the sensor locations fully decoupled from the actuator locations for the purpose of passively compensating for the load frame compliance, as a result improving the effective stiffness of the manipulator in six degrees of freedom (6DOF). In this paper, the stiffness of the proposed manipulator is quantified via a simplified method, which combines both an analytical model (robot kinematics error model) and a numerical model [finite element analysis (FEA) model] in the analysis. This method can be used to design systems with specific stiffness requirements. In the control aspect, the noncollocated positions of the sensors and actuators lead to a suboptimal control structure, which is addressed in the paper using a simple Jacobian-based decoupling method under both kinematics-and dynamics-based control. Simulation results demonstrate that the proposed manipulator configuration has an effective stiffness that is increased by a factor of greater than 15 compared to a general design. Experimental results show that the Jacobian-based decoupling method effectively increases the dynamic tracking performance of the manipulator by 25% on average over a conventional method.
机译:当施加较大的外力/扭矩时,机器人框架的顺应性会对系统的整体精度产生很大的负面影响。这种现象在需要机器人在非常大的外部负载下实现超高(微米级)精度的应用中尤其成问题,例如在生物力学测试和高精度加工中。为了确保机器人在这些应用中的定位精度,作者提出了一种新颖的基于Stewart平台的机械手,该传感器具有分离的传感器-执行器位置。独特的机制使传感器位置与执行器位置完全脱开,以被动地补偿负载框架的柔度,从而在六个自由度(6DOF)中提高了机械手的有效刚度。在本文中,通过简化方法对所提出的机械手的刚度进行了量化,该方法在分析中结合了解析模型(机器人运动学误差模型)和数值模型(有限元分析模型)。此方法可用于设计具有特定刚度要求的系统。在控制方面,传感器和执行器的并列位置会导致次优控制结构,本文使用基于运动学和动力学的简单的基于Jacobian的解耦方法解决了该问题。仿真结果表明,与常规设计相比,所提出的机械手配置具有有效的刚度,该刚度提高了15倍以上。实验结果表明,基于雅可比行列的解耦方法比传统方法平均有效地将机械手的动态跟踪性能提高了25%。

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