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Decentralized Fuzzy Control of Multiple Cooperating Robotic Manipulators With Impedance Interaction

机译:具有阻抗交互作用的多机器人机器人的分散模糊控制。

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摘要

In this paper, a decentralized adaptive fuzzy control has been developed for two cooperating robotic manipulators moving an object with impedance interaction. The contact forces are described using gradients of nonlinear potentials; then, the deformations of the contact surface can be obtained by an impedance approach. The cooperating manipulators are considered as a combination of subsystems, and the decentralized local dynamics coupled with physical interactions among the subsystems are developed. To compensate for the effect of dynamics uncertainties and external disturbances, decentralized fuzzy control combining parameter adaptations and disturbance observers is constructed. It guarantees the motion trajectories and impedance forces of the constrained object converging to the desired manifolds. It is theoretically established that the disturbance observers compensate for unparameterizable uncertainties, while the adaptive fuzzy mechanism compensates for the fast-changing components of the uncertainties that go beyond the disturbance observers. Moreover, unknown nonlinear dynamics such as the inertia matrix, Coriolis/centripetal matrix, and frictions, as well as interconnections with nonlinear bounds, can be accommodated through online learning. The experiments on two real robots have been carried out to verify the effectiveness of the proposed theoretical results.
机译:在本文中,已经开发了一种分散自适应模糊控制,用于两个协作的机械手以阻抗交互作用移动对象。接触力是使用非线性电势的梯度来描述的。然后,可以通过阻抗方法获得接触表面的变形。协作操纵器被视为子系统的组合,并且开发了分散的局部动力学以及子系统之间的物理交互作用。为了补偿动力学不确定性和外部干扰的影响,构建了将参数自适应和干扰观测器相结合的分散模糊控制。它保证了被约束物体的运动轨迹和阻抗力收敛到所需的歧管。从理论上讲,干扰观测器补偿了不可参数化的不确定性,而自适应模糊机制则补偿了干扰观测器以外的不确定性的快速变化成分。此外,可以通过在线学习来适应未知的非线性动力学,例如惯性矩阵,科里奥利/向心矩阵,摩擦以及具有非线性边界的互连。已经在两个真实的机器人上进行了实验,以验证所提出的理论结果的有效性。

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