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Hybrid Force/Position Control of Industrial Robotic Manipulator Based on Kalman Filter

机译:基于卡尔曼滤波器的工业机器人机械手混合动力/位置控制

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This paper proposes a hybrid force/position controller for industrial robotic manipulator based on Kalman filter. Firstly, the mathematical model of real contact force is built to estimate the actual contact force by applying Kalman filter using a force derivative to achieve the system state description. The estimated actual contact force is used to control the end-effector force as well as estimating the stiffness of environment. To refine the environment stiffness estimation the Recursive Least Square (RLS) technique has been employed. Owing to the fact that the general industrial manipulator only provides the position control mode, the position-based hybrid force/position control architecture is designed and realized by using the position tracking mode of the motion control card. The main advantages of the implemented controller is simplicity, computational efficiency and robustness to unknown environment, it is convenience for the general industrial manipulators. Besides, it lends itself for industrial manipulators in order to achieve compliant behavior and perform complex tasks. The proposed control structure is successfully validated by practical experiments. The results show that the controller has a satisfactory performance in term of force control and trajectory tracking and robustness to force/torque sensor measurement interferences.
机译:本文提出了一种基于卡尔曼滤波器的工业机器人机械手的混合动力/位置控制器。首先,建立实际接触力的数学模型来估计通过使用力导数应用卡尔曼滤波器来实现系统状态描述来估计实际接触力。估计的实际接触力用于控制末端效应器力以及估计环境刚度。为了优化环境刚度估计,已经采用了递归最小二乘(RLS)技术。由于通用工业机械手仅提供位置控制模式,通过使用运动控制卡的位置跟踪模式设计和实现基于位置的混合力/位置控制架构。所实施的控制器的主要优点是简单,计算效率和鲁棒性对未知环境,是通用工业机械手的便利性。此外,它适用于工业机械手,以实现柔顺的行为并执行复杂的任务。通过实际实验成功验证了所提出的控制结构。结果表明,控制器在力控制和轨迹跟踪和鲁棒性方面具有令人满意的性能,以力/扭矩传感器测量干扰。

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